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Mathematical and Computational Sciences

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The School of Mathematical and Computational Sciences is located in Cass Science Hall.

The School of Mathematical and Computational Sciences (SMCS) is built on a strong foundation of core Mathematics and Computer Science programs that have existed at UPEI for many years. The SMCS is unique in Atlantic Canada for offering a comprehensive suite of majors in the quantitative disciplines.

Mathematical and computational sciences are experiencing a “boom”, as many industries and sectors need people with the skills to manage, analyze, and extract useful information from data. This is what mathematicians, statisticians, and computer scientists are trained to do. Analytics (sometimes called “data science”) is at the intersection of mathematics, statistics, and computer science, and is the hottest area of job growth right now.

We offer the only complete actuarial degree in Atlantic Canada. The unemployment rate for actuaries in Canada is 0%, and the mid-career average salary is near $100,000. When our program is accredited by the Canadian Institute of Actuaries, UPEI will be one of only 12 universities in Canada with an accredited program in actuarial science.

Visit the "Programs" tab to learn about our degrees.  

Want more information about Mathematical and Computational Sciences? Leave your email address and we'll get in touch!
First Name:
Last Name:
E-mail Address:
Careers:
  • Mathematician
  • Video Game Designer
  • Statistician
  • Actuary
  • Web Developer
  • Financial Manager
  • ... and many more!
The School of Mathematical and Computational Sciences is located in Cass Science Hall.

The School of Mathematical and Computational Sciences offers degrees in:


Course code prefixes

In the School of Mathematical and Computational Sciences, there are five course prefixes:

  • MATH – for Mathematics courses
  • STAT – for Statistics courses
  • CS – for Computer Science courses
  • AMS – for Applied Mathematical Sciences courses (mainly Actuarial Science and Financial Mathematics)
  • MCS – for common or interdisciplinary courses in Mathematical and Computational Science

Common requirements across all degree programs in the School of Mathematical and Computational Sciences

COMMON CORE

All degree programs in the School of Mathematical and Computational Sciences are built on a common core of courses that should be completed in the first two years of study. This common core consists of the following courses:

Course Course name Credits
MATH 1910 Single Variable Calculus I 4
MATH 1920 Single Variable Calculus II 4
MATH 2610 Linear Algebra I 3
STAT 2210 Introductory Statistics 3
CS 1910 Computer Science I 3
CS 1920 Computer Science II 3

One of:
UPEI 1010
UPEI 1020
UPEI 1030


Writing Studies
Inquiry Studies
University Studies

3
Total Semester Hours of Credit   23

COMMON BREADTH REQUIREMENT

Students must take at least 15 semester hours of credit in courses outside the School of Mathematical and Computational Sciences (excluding one of the UPEI courses listed above), and of these 15 semester hours of credit, at least 6 must be from Biology, Chemistry or Physics and at least 6 must be from outside the Faculty of Science.

COMMON ADVANCED COURSES

Students in all degree programs in the School of Mathematical and Computational Sciences must complete MCS 4210 Professional Communication and Practice (writing-intensive) and MCS 3050 Tutoring in Mathematical and Computational Sciences. 


REQUIREMENTS FOR A MAJOR IN MATHEMATICS

Mathematics is the study of quantity, structure and space. While mathematics is important in understanding and influencing the physical world around us, mathematics can also be curiosity-driven and enjoyed without the requirement of a particular application. The Bachelor of Science with a major in Mathematics provides students with a solid foundation in both pure and applied mathematics, preparing them for graduate studies and professional programs. Students interested in graduate studies in mathematics should consider the Bachelor of Science with honours in Mathematics.

The Major in Mathematics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910- Multivariable and Vector Calculus 4

MATH 2620 - Linear Algebra II

3
MATH 2720 - Mathematical Reasoning  3

At least one of:  MCS 2010 - MAPLE Technology Lab or  MCS 2020  - Matlab Technology Lab

1
MATH 2420 - Combinatorics I   3
STAT 2220 - Introductory Statistics II 3
MATH 3510 - Real Analysis       3
MATH 3610 - Group Theory     3

At least one of : MATH 3010 - Differential Equations, STAT  3210 - Probability and Mathematical Statistics I or  MATH 3310 - Complex Variables

3

Five electives in the Mathematical and Computational Sciences (at the 2000 level or higher with at least two at the 3000 level or higher)

15
MCS 3050 - Tutoring in Mathematical and Computational Sciences    1
MCS 4210 - Professional Communication and Practice 3
Additional general electives                         52
Total Semester Hours of Credit       120

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REQUIREMENTS FOR A MAJOR IN STATISTICS

Statistics is the practice of collecting and analyzing numerical data, and inferring properties of the whole from a representative sample. The Bachelor of Science with a major in Statistics provides students with the solid foundation in both statistical theory and applied statistics necessary to become a statistician or proceed to more specialized statistical study at the graduate level. Students interested in continuing to work in statistics research should consider the Bachelor of Science with honours in Statistics.

The Major in Statistics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3
MCS 2030 - R Technology Lab 1
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I                 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4550 - Data Analysis and Inference 3
STAT 4240 - Experimental Design 3
STAT 4330 - Time Series I       3
STAT 4110 - Statistical Simulation 3
STAT 4410 - Stochastic Processes 3

Two electives in the Mathematical and Computational Sciences (at the 2000 level or higher)           

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit       120

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REQUIREMENTS FOR A MAJOR IN COMPUTER SCIENCE

Computer Science is a key enabler for innovation and discovery in most fields. It encompasses both theory and practice; theoretical ideas about how information is represented and processed, and practical techniques for creating new software. The School offers options such as co-operative education, a specialization in video game programming, and an Honours degree. Employment prospects are among the highest of any field. Honours graduates are well positioned to pursue graduate studies.

The Major in Computer Science requires a total of 120 semester hours of credit, as described below.  

  Credits
The Common Core 23
CS 1610 - Digital Systems 3
CS 2520 - Computer Organization and Architecture 3
CS 2610 -  Data Structures and Algorithms 3
CS 2620 - Comparative Programming Languages 3
CS 2820 - Programming Practices 3
MATH 2420 - Combinatorics I 3
MCS 3320 - Theory of Computing 3
CS 3420 - Computer Communications         3
CS 3520 - Operating Systems 3
CS 3610 - Analysis and Design of Algorithms             3
CS 3620 - Software Design and Architecture 3
CS 3710 - Database Systems 3
CS 4810 - Software Engineering 3

One of: 

CS 4820 - Software Systems Development Project or 
CS 4840 - Prototype Systems Development            

 

3
6

Two electives in Mathematical and Computational Sciences (at the 2000 level or higher)                          

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives: if CS 4820 taken 45
or if CS 4840 taken 42
Total Semester Hours of Credit    

120

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REQUIREMENTS FOR A MAJOR IN ACTUARIAL SCIENCE

Actuarial Science is the study of risk, usually risk associated with insurance, pension, and investment plans. Actuarial Science uses techniques from mathematics, statistics, business, economics, and finance. The Bachelor of Science with a Major in Actuarial Science prepares students to write the early exams required to become an Actuary. Actuaries are in demand as professionals who develop solutions for complex financial issues. Actuaries have excellent career opportunities following graduation as well as excellent co-op work opportunities during their studies. Read more about what actuaries' do, job prospects, and salaries on our departmental website.

The Major in Actuarial Science requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I 3
STAT 3220 - Probability and Mathematical Statistics II 3
STAT 3240 - Applied Regression Analysis 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning               3
MATH 3010 - Differential Equations 3

At least one of: 

MCS 2020 - Matlab Technology Lab
MCS 2040 - Visual Basic in Excel Technology Lab
OR MCS 2050 - GGY AXIS Technology Lab                    

1
AMS 2160 - Mathematics of Finance 3
AMS 2400 - Financial Mathematics & Investments 3
AMS 2410 - Financial Economics I       3
AMS 3410 - Financial Economics II 3
AMS 2510 - Actuarial Science I 3
AMS 3510 - Actuarial Science II 3
AMS 3310 - Advanced Corporate Finance for Actuaries 3
AMS 3730 - Advanced Insurance and Actuarial Practices 3
AMS 4540 - Loss Models I      3
AMS 4550 - Loss Models II 3
AMS 4580 - Credibility Theory 3
STAT 4110 - Statistical Simulation 3
STAT 4330 - Time Series I       3
STAT 4410 - Stochastic Processes       3
MCS 3920 - Numerical Analysis 3
ECON 1010 - Introductory Microeconomics  3
ECON 1020 - Introductory Macroeconomics 3
ACCT 1010 - Introduction to Accounting 3
BUS 2310 - Corporate Finance 3
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives 10
Total Semester Hours of Credit        120

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REQUIREMENTS FOR A MAJOR IN FINANCIAL MATHEMATICS

Financial Mathematics is the application of mathematical models to finance, usually to analyze markets and pricing. Financial Mathematics uses techniques from mathematics, statistics, business, finance, and economics. The Bachelor of Science in Financial Mathematics provides a solid foundation in Financial Mathematics, leading either to a career in the financial sector or to further training in advanced Financial Mathematics. Financial Mathematicians are in demand as professionals who develop solutions for complex financial issues and they have excellent career opportunities following graduation as well as excellent co-op work opportunities during their studies.

The Major in Financial Mathematics requires a total of 120 semester hours of credit, as described below:

  Credit Hours
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning               3
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I              3
STAT 3220 - Probability and Mathematical Statistics II             3
STAT 3240 - Applied Regression Analysis 3

At least one of: 

MCS 2020 - Matlab Technology Lab
MCS 2030 - R Technology Lab
OR MCS 2040 - Visual Basic in Excel Technology Lab

1
AMS 2160 - Mathematics of Finance 3
AMS 2400 - Financial Mathematics & Investments 3
AMS 2410 - Financial Economics I 3
AMS 3410 - Financial Economics II 3
AMS 4080 - Financial Mathematics II 3
AMS 4090 - Financial Mathematics III               3
AMS 4780 - Quantitative Risk Management 3
AMS 3910 - Mathematical Modelling 3
AMS 3310 - Advanced Corporate Finance for Actuaries 3
MATH 3010 - Differential Equations 3
MATH 3510 - Real Analysis  3
MATH 4710 - Partial Differential Equations 3
STAT 4330 - Time Series I       3

At least one of:

STAT 4410 - Stochastic Processes
OR MATH - 3920 Numerical Analysis

3
ECON 1010 - Introductory Microeconomics  3
ECON 1020 - Introductory Macroeconomics 3

At least one of:

ECON 2510 - Money and Financial Institutions
OR ECON 4050 - Financial Economics

3
ACCT 1010 - Introduction to Accounting           3
BUS 2310 - Corporate Finance 3

At least one of: 

BUS 3330 - Integrated Cases in Corporate Finance
BUS 3660 - Entrepreneurial Finance
BUS 4210 - Personal Finance
BUS 4390 - International Finance
OR BUS 4820 - International Strategy and Finance     

3
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives         10
Total Semester Hours of Credit 120

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REQUIREMENTS FOR A MAJOR IN ANALYTICS

(Specialization in Data Analytics)

Analytics is situated at the confluence of statistics, computer science and mathematics all centered on finding, interpreting and presenting meaningful patterns in data. We offer a Bachelor of Science in Analytics with specialization in either Data Analytics or Business Analytics, with co-operative education options available in both specializations. As data increasingly pervades our lives, graduates in Analytics are in high demand across a broad spectrum of fields including government, business and technology.

The Major in Analytics with a specialization in Data Analytics requires a total of 120 semester hours of credit, as described below: 

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3

At least one of: 

MCS 2010 - MAPLE Technology Lab
MCS 2020 - Matlab Technology Lab
OR MCS 2030 - R Technology Lab       

1
MATH 2420 -  Combinatorics I 3
MATH 3430 - Combinatorics II 3
AMS 2940 - Optimization       3
AMS 3770 - Combinatorial Optimization 3
AMS 3910 - Mathematical Modelling 3
MATH 3010 - Differential Equations 3
MATH 3610 - Group Theory     3
STAT 3210 - Probability and Mathematical Statistics I 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4550 - Data Analysis and Inference 3
STAT 4660 - Data Visualization and Mining 3
CS 2610 - Data Structures and Algorithms 3
CS-2910 - Computer Science III 3
CS 3710 - Database Systems 3
CS 3610 - Analysis and Design of Algorithms             3
CS 4120 - Machine Learning 3
CS 4440 - Data Science 3

Two  electives in Mathematical or Computational Sciences (at the 2000 level or higher)

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences    1
MCS 4210 - Professional Communication and Practice             3
Additional general electives 19
Total Semester Hours of Credit      120

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REQUIREMENTS FOR A MAJOR IN ANALYTICS

(Specialization in Business Analytics)

The Major in Analytics with a specialization in Business Analytics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II                 3
MATH 2620 - Linear Algebra II                3
MATH 2720 - Mathematical Reasoning  3

At least one of:

MCS 2010 - MAPLE Technology Lab
MCS 2020 - Matlab Technology Lab 
OR MCS 2030 - R Technology Lab         

1
MATH 2420 - Combinatorics I 3
MATH 3430 - Combinatorics II 3
AMS 2940 - Optimization       3
AMS 3770 - Combinatorial Optimization 3
AMS 3910 - Mathematical Modelling 3
MATH 3010 - Differential Equations 3
STAT 3210 - Probability and Mathematical Statistics I                 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4660 - Data Visualization and Mining 3

Two electives in the Mathematical and Computational Sciences (at the 3000 level or higher)

6
CS 2610 - Data Structures and Algorithms 3
CS 2910 - Computer Science III 3
CS 3710 - Database Systems 3
ACCT 1010 - Introduction to Financial Accounting 3
BUS 1410 - Marketing 3
BUS 1710 - Organizational Behaviour 3

At least five of: 

ACCT 2210 - Managerial Accounting
BUS 2650 - Introduction to Entrepreneurship
BUS 2880 - Research and Evidence-Based Management
BUS 2720 - Human Resource Management
BUS 3010 - Business Law
BUS 3330 - Integrated Cases in Corporate Finance
BUS 3510 - Operations Management
BUS 3710 - Entrepreneurship and New Ventures
BUS 4650 - Project Management
OR BUS 4880 - Developing Management Skills

15
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives 10
Total Semester Hours of Credit       120

Note: Students who complete the Major in Analytics with a specialization in Business Analytics and obtain grades of at least 60% in seven of the Business courses can also obtain a Certificate in Business.

 

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REQUIREMENTS FOR A MAJOR IN MATHEMATICS WITH ENGINEERING

The specialization augments the Mathematics major with Engineering courses offered through UPEI’s School of Sustainable Design Engineering. The Bachelor of Science in Mathematics with Engineering provides a foundational Engineering program combined with more advanced mathematical training than is received in an Engineering Degree program.

The Major in Mathematics with Engineering requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
STAT 2220 - Introductory Statistics II 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3
MATH 3010 - Differential Equations 3
MATH 3310 - Complex Variables 3

At least one of:

MATH 3510 - Real Analysis
OR Math 3610 Group Therapy

3

Two electives in Mathematical and Computational Sciences (at the 3000 level or higher)

6
PHYS 1110 and 1120 - General Physics I and II 6
CHEM 1110 and 1120 - General Chemistry I and II 6
ENGN 1210 - Design 1: Engineering Communications 3
ENGN 1220 - Design 2: Engineering Analysis 3
ENGN 1510 - Engineering and the Biosphere 3
ENGN 2210 - Design 3: Engineering Projects I 3
ENGN 2220 - Design 4: Engineering Projects II 3
ENGN 2310 - Strength of Materials 3
ENGN 2340 - Engineering Dynamics 3
ENGN 2610 - Thermofluids I 3
ENGN 2810 - Electrical Circuits I 3
Two electives in Engineering        6
Additional general electives 24
Total Semester Hours of Credit       120

Note: Mathematics with Engineering Majors may substitute ENGN 1320 for CS 1510, and CS 1610 or MCS 3920 for CS 1520.

 

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REQUIREMENTS FOR A MAJOR IN COMPUTER SCIENCE (Specialization in Video Game Programming)

The Major in Computer Science with a specialization in Video Game Programming requires a total of 120 semester hours of credit, as described below.  

  Credits
The Common Core 23
CS 1610 - Digital Systems 3

At least one of:

CS 2120 - Mobile Device Development – iOS 
OR CS 2130 - Mobile Device Development – Android

3
CS 2520 - Computer Organization and Architecture 3
CS 2610 - Data Structures and Algorithms 3
CS 2620 - Comparative Programming Languages 3
CS 2820 - Programming Practices 3
MATH 2420 - Combinatorics I 3
CS 3110 - Video Game Design 3
MCS 3320 - Theory of Computing 3
CS 3420 - Computer Communications         3
CS 3520 - Operating Systems 3
CS 3610 - Analysis and Design of Algorithms 3
CS 3620 - Software Design and Architecture 3
CS 3710 - Database Systems 3
CS 4350 - Computer Graphics Programming 3
CS 4360 -  Advanced Computer Graphics Programming 3

At least two of: 

CS 4060 - Cloud Computing
CS 4120 - Machine Learning
CS 4440 - Data Science
OR CS 4610 - Wireless Sensor Networks

6
CS 4650 - Video Game Architecture 3
CS 4810 - Software Engineering 3
CS 4830 - Video Game Programming Project            6

Two electives in the Mathematical and Computational Sciences (at the 2000 level or higher)

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives 21
Total Semester Hours of Credit 120

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Acceptance to an Honours program

Students in the Mathematics, Statistics and Computer Science programs have an Honours option. Permission of the School of Mathematical and Computational Sciences is required for admission to an Honours program. Students must normally have a minimum average of 70% in all previous courses. Normally, the School expects an average of 75% in all previous Mathematical and Computational Sciences courses. Admission is contingent upon the student finding a project advisor and acceptance by the School of the topic for the Honours project. Students interested in doing Honours are strongly encouraged to consult with the Associate Dean of the School of Mathematical and Computational Sciences as soon as possible, and no later than January 31 of the student’s third year. To receive the Honours designation, in addition to successful completion of the Honours project, normally students must maintain an average of at least 75% in all courses in the School of Mathematical and Computational Sciences.

REQUIREMENTS FOR HONOURS IN MATHEMATICS

The Honours in Mathematics program requires a total of 126 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910  Multivariable and Vector Calculus              4
STAT 2220     Introductory Statistics II                 3
MATH 2620   Linear Algebra II 3
MATH 2720   Mathematical Reasoning  3

At least one of: MCS 2010 - MAPLE Technology Lab OR MCS 2020 - Matlab Technology Lab

1
MATH 2420  Combinatorics I 3
MATH 3510   Real Analysis  3
MATH 3610  Group Theory 3
MATH 3010  Differential Equations 3
STAT   3210  Probability and Mathematical Statistics I 3
MATH 3310  Complex Variables 3
MCS 4900     Honours Project 6

Four electives in the Mathematical and Computational Sciences (at the 2000 level or higher, with at least two at the 4000 level or higher)

12
MCS 3050  Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit    126

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REQUIREMENTS FOR HONOURS IN STATISTICS

The Honours in Statistics program requires a total of 126 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910  Multivariable and Vector Calculus 4
STAT 2220    Introductory Statistics II 3
MATH 2620  Linear Algebra II 3
MATH 2720  Mathematical Reasoning  3
MCS 2030    R Technology Lab 3
STAT 3210  Probability and Mathematical Statistics I                 3
STAT 3220  Probability and Mathematical Statistics II 3
STAT 3240   Applied Regression Analysis 3
STAT 4550  Data Analysis and Inference 3
STAT 4240  Experimental Design       3
STAT 4330  Time Series I       3
STAT 4110   Statistical Simulation 3
STAT 4410   Stochastic Processes 3
MCS 4900   Honours Project 6

Two electives in the Mathematical and Computational Science (at the 3000 level or higher)

6
MCS 3050  Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit 126

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REQUIREMENTS FOR HONOURS IN COMPUTER SCIENCE

The Honours in Computer Science requires a total of 126 semester hours of credit, as described below.  
 

  Credits
The Common Core 23
CS 1610 Digital Systems 3
CS 2520  Computer Organization and Architecture 3
CS 2610   Data Structures and Algorithms 3
CS 2620   Comparative Programming Languages 3
CS 2820   Programming Practices 3
MATH 2420  Combinatorics I 3
MATH 2910  Multivariable Calculus 4
MCS 3320   Theory of Computing 3
CS 3420   Computer Communications 3
CS 3520   Operating Systems 3
CS 3610   Analysis and Design of Algorithms             3
CS 3620   Software Design and Architecture 3
CS 3710   Database Systems 3

At least one of: CS 4110 - Artificial Intelligence and Automated Reasoning OR CS 4120 - Machine Learning

3
CS 4810   Software Engineering 3
MCS 4900  Honours Research Project 6

Four electives in the Mathematical and Computational Sciences (at the 2000 level or higher)

12
MCS 3050 Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives 35
Total Semester Hours of Credit     126

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REQUIREMENTS FOR A MINOR IN MATHEMATICS

Students may obtain a Minor in Mathematics by completing at least 24 semester hours of credit in Mathematics defined as follows:

Math 1910-1920 - Single Variable Calculus I & II 8
Math 2610 - Linear Algebra I 3
Math 2910 - Multivariable and Vector Calculus 4
plus 3 semester hours of credit in Mathematics at the 3000 level or higher, and an additional 6 semester hours of credit of Mathematics at the 2000 level or above 9
Total Semester Hours of Credit 24

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REQUIREMENTS FOR A MINOR IN STATISTICS

Students may obtain a Minor in Statistics by completing at least 23 semester hours of credit in Mathematics and Statistics defined as follows:

MATH 1910-1920 - Single Variable Calculus I  & II 8
STAT 2210-2220 - Introductory Statistics I & II 6
MATH 2610 - Linear Algebra I 3
STAT 3210 -  Probability and Mathematical Statistics I 3
plus 3 semester hours of credit in Statistics at the 3000 level or higher 3
Total Semester Hours of Credit 23

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REQUIREMENTS FOR A MINOR IN COMPUTER SCIENCE

Students may obtain a Minor in Computer Science by completing at least 21 semester hours of credit in Computer Science defined as follows:

CS 1910-1920 - Computer Science I & II  6
CS 2520 - Computer Organization and Architecture  3
CS 2610 - Data Structures and Algorithms  3

plus 3 semester hours of credit in Computer Science at the 3000 level or higher, and an additional 6 semester hours of credit in Computer Science at the 2000 level or higher

9
Total Semester Hours of Credit  21
 

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MATHEMATICAL AND COMPUTATIONAL SCIENCES CO-OP PROGRAM

The Mathematical and Computational Sciences Co-op program is an integrated approach to university education that enables students to alternate academic terms on campus with work terms in relevant and supervised employment. The Co-op program consists of eight academic terms, at least three work terms and a series of professional development workshops and seminars. It is available as an option to full-time students enrolled in Major and Honours programs. Application to the co-op program is made in the student’s second year of study. Students must complete 126 semester hours of credit to graduate with the Co-op designation, and no credit will be given for any Co-op work term course, unless at least three work terms are successfully completed.

See the Co-op Education (Mathematical and Computational Sciences) page for complete program details.

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ADMISSION TO SCIENCE CALCULUS

The First-year Calculus courses for most science students are Math 191 and Math 1920. In addition to Grade XII academic Mathematics (or equivalent), a passing grade on an Assessment Test written during the first week of classes is required as a prerequisite for Math 1910. The Assessment Test covers the standard pre-calculus topics of the High School curriculum (arithmetic, algebra, trigonometry, analytic geometry and the basic theory of functions). This test is of 90 minutes duration and is given during the first week of classes.

Students who do not pass the assessment test may have the option of enrolling in a special section of Math 1910 incorporating additional tutorials reviewing pre-Calculus materials. See the Associate Dean of the School of Mathematical and Computational Sciences for details.


 

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Careers:
  • Mathematician
  • Video Game Designer
  • Statistician
  • Actuary
  • Web Developer
  • Financial Manager
  • ... and many more!
The School of Mathematical and Computational Sciences is located in Cass Science Hall.

Course code prefixes

In the School of Mathematical and Computational Sciences, there are five course prefixes:

Mathematics (MATH) Courses

MATH-1010 - ELEMENTS OF MATHEMATICS This course provides an introduction to several mathematical topics at the university level, and is intended for students majoring in a discipline other than Mathematical and Computational Sciences, or the Natural Sciences. The course consists of four modules: (1) Sets and Logic, (2) Number Theory, (3) Geometry, (4) Mathematical Systems. NOTE: Credit will not be given jointly for this course and any other 1000-level Mathematics course. Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1110 - FINITE MATHEMATICS This course introduces students to finite mathematical techniques and to mathematical models in business, life and the social sciences. The course begins with an introduction to mathematical models, types of models, and conversion of verbal models to mathematical models. Topics covered include systems of linear equations and matrices, linear inequalities and linear programming, sets, counting and probability. NOTE: Credit for Mathematics 1110 will not be allowed if taken concurrent with or subsequent to Mathematics 2610. Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1120 - CALCULUS FOR THE MANAGERIAL, SOCIAL AND LIFE SCIENCES This course provides an introduction to calculus for students in the managerial, social and life sciences. The main emphasis of the course is the development of techniques of differentiation and integration of algebraic, exponential and logarithmic functions. Applications of derivatives and integrals are also discussed. NOTE: Credit will not be given jointly for this course and Math 1910 Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1910 - SINGLE VARIABLE CALCULUS I This course is an introduction to differential and integral calculus of functions of a single variable. The course is intended primarily for majors in the Mathematical and Computational Sciences, Engineering and the Physical Sciences, as well as those planning to continue with further Mathematics courses. The concepts of limits, continuity and derivatives are introduced and explored numerically, graphically and analytically. The tools of differential calculus are applied to problems in: related rates; velocity and acceleration; extrema of functions; optimization; curve sketching; and indeterminate forms. The concepts of definite and indefinite integrals are introduced, and the relation between the two integrals is discovered via the Fundamental Theorem of Calculus. Four lecture hours per week Semester hours of credit: 4 Prerequisite: Prerequisite: Grade XII academic Mathematics [and a passing grade on the Assessment Test]
PREREQUISITE: Math-1910T (concurrent with taking this course)
4 hours credit
MATH-1910R - PRE-CALCULUS REVIEW TUTORIAL
MATH-1910T - MATH 1910 TUTORIAL
PREREQUISITE: Math 1910 (concurrent with taking this course)
MATH-1920 - SINGLE VARIABLE CALCULUS II This course is a continuation of integral calculus of functions of a single variable and an introduction to sequences and series. Techniques of integration are studied, including improper integrals and numerical integration, and the tools of integral calculus are used to compute areas, volumes and arc lengths; and are applied to problems in physics and differential equations. Sequences, series, tests for convergence, Taylor series and Taylor polynomials are studied. Four lecture hours per week Semester hours of credit: 4
PREREQUISITE: Math-1920T (concurrent with taking this course)
4 hours credit
MATH-1920T - Math 1920 Tutorial
PREREQUISITE: Mathematics 1920 (concurrent with taking this course)
MATH-2420 - COMBINATORICS I This course offers a survey of topics in discrete mathematics that are essential for students majoring in the Mathematical and Computational Sciences. Topics include: logic, proof techniques such as mathematical induction, recursion, counting methods, and introductory graph theory. Three lecture hours per week
PREREQUISITE: Math 1920 (prior to taking this course)
3 hours credit
MATH-2610 - LINEAR ALGEBRA I This course introduces some of the basic concepts and techniques of linear algebra to students of any major. The emphasis is on the interpretation and development of computational tools. Theory is explained mainly on the basis of two or three-dimensional models. Topics covered are: matrices; determinants; systems of equations; vectors in two and three-dimensional space including dot and cross products, lines, and planes; concepts of linear independence, basis, and dimension explained with examples; linear transformations and their matrices; eigenvectors and eigenvalues. Three lecture hours per week Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-2620 - LINEAR ALGEBRA II This course continues MATH 2610 with further concepts and theory of linear algebra. Topics include vector spaces, orthogonality, Gram-Schmidt Process, canonical forms, spectral decompositions, inner product spaces and the projection theorem. Three lecture hours a week
PREREQUISITE: Math 1910 and Math 2610 (prior to taking this course)
3 hours credit
MATH-2720 - MATHEMATICAL REASONING This course provides students with experience in writing mathematical arguments. It covers first-order logic, set theory, relations, and functions. The ideas and proof techniques are considered in the context of various mathematical structures such as partial orders, graphs, number systems, and finite groups. Three lecture hours per week
3 hours credit
MATH-2810 - FOUNDATIONS OF GEOMETRY This course presents an axiomatic base for Euclidean geometry and an insight into the interdependence of the various theorems and axioms of that geometry and non-Euclidean geometries. Topics include: incidence and separation properties for points, lines, planes and space; congruence properties; geometric inequalities; similarity properties; and geometric constructions. Three lecture hours per week
PREREQUISITE: Six credit hours of First Year Mathematics (prior to taking this course)
3 hours credit
MATH-2820 - MATHEMATICAL PHYSICS (FORMERLY 3810) (Please note this course will not be offered until January, 2017) This course is an introduction to some of the mathematical methods commonly used in the physical sciences and engineering, with an emphasis on applications in physics. Topics include: vector analysis in curvilinear coordinates, tensor analysis (with applications in fluid mechanics), introduction to complex variables, Fourier series, calculus of variations and applications. Cross-listed with Physics (cf. Physics 2820) Three hours lecture per week
PREREQUISITE: Math 2910 and either Physics 1120 or Physics 1220 (prior to taking this course)
3 hours credit
MATH-2910 - MULTIVARIABLE AND VECTOR CALCULUS This course continues from Math 1920 and is an introduction to multivariable differentiation and integration and vector calculus. Topics include parametric representation of curves; polar coordinates; vectors; dot and cross products; curves and surfaces in space; calculus of vector-valued functions; functions of several variables; partial differentiation; directional derivatives; tangent planes; local and constrained maxima and minima; double and triple integrals; changes of variables in multiple integrals; vector fields; line and surface integrals; gradient, divergence and curl; Green's, Stokes' and Divergence Theorems. Four lecture hours per week Semester hours of credit: 4
PREREQUISITE: Math 1920 (prior to taking this course)
4 hours credit
MATH-2910T - ADDITIONAL LECTURE
MATH-3010 - DIFFERENTIAL EQUATIONS This course introduces the basic theory of differential equations, considers various techniques for their solution, and provides elementary applications. Topics include linear equations; separable equations; linear independence and Wronskian; second-order equations with constant coefficients; nonhomogeneous equations; applications of first- and second-order equations; Laplace and inverse Laplace transforms, and their application to initial-value problems; series solutions about ordinary and singular points; and Fourier series. Three lecture hours per week
PREREQUISITE: Math 1920 (prior to taking this course)
3 hours credit
MATH-3210 - PROBABILITY AND MATH STATS I
3 hours credit
MATH-3220 - PROBABILITY AND MATH STATS II
3 hours credit
MATH-3240 - APPLIED REGRESSION ANALYSIS
3 hours credit
MATH-3310 - COMPLEX VARIABLES This is a first course in complex variables. The aim is to acquaint students with the elementary complex functions, their properties and derivatives, and with methods of integration. Topics covered include: definition and development of complex numbers as ordered pairs; geometric representation; basic formulas and inequalities involving argument and conjugates; roots of complex numbers, limit, continuity, and derivative; Cauchy Riemann conditions; harmonic functions; properties of trigonometric, hyperbolic, logarithmic, exponential, and inverse trigonometric functions; bilinear transformation; integration; Cauchy Integral Theorem and Formula; residues and poles; Laurent and Taylor's series; and improper integrals. Three lecture hours per week
PREREQUISITE: Math 2910 (prior to taking this course)
3 hours credit
MATH-3420 - NUMBER THEORY This first course in number theory will include the following topics: equivalence of the principles of induction and the well-ordering principle; division algorithm; positional notation and repeating decimals; greatest common divisor; Euclidean Algorithm; Fundamental Theorem of Arithmetic; Pythagorean Triplets; Prime Numbers Theorem; Mersenne and Fermat Numbers; congruences; Euler's Phi-function; Chinese Remainder Theorem; Diophantine Equations; Theorems of Lagrange and Wilson; Quadratic Reciprocity Law of Gauss; Legendre symbol and primitive roots; perfect numbers; multiplicative number- theoretic functions; Moebius inversion. Three lecture hours per week
PREREQUISITE: Six credit hours of Mathematics at the 2000 level or higher (prior to taking this course)
3 hours credit
MATH-3430 - COMBINATORICS II This course continues MATH 2420, with the examination of advanced counting techniques, binomial coefficients, and generating functions. Other topics include relations, partial orders, and Steiner Triple systems. Three lecture hours per week
PREREQUISITE: Math 2420 (prior to taking this course)
3 hours credit
MATH-3510 - REAL ANALYSIS This is a first course in real analysis. Topics include: the reals as a complete ordered field; closed and open sets; Bolzano-Weierstrass and Heine-Borel Theorems; Cauchy Sequences; limits and continuity; derivative; Mean Value Theorem; Riemann Integral; and the Fundamental Theorem of Calculus. Three lecture hours per week
PREREQUISITE: Math 1920 and Math 2720 (prior to taking this course)
3 hours credit
MATH-3520 - REAL ANALYSIS II
3 hours credit
MATH-3610 - GROUP THEORY An introduction to group theory, including: cyclic groups, symmetric groups, subgroups and normal subgroups, Lagrange's theorem, quotient groups and homomorphisms, isomorphism theorems, group actions, Sylow's theorem, simple groups, direct and semidirect products, fundamental theorem on finitely generated Abelian groups. Three lecture hours per week
PREREQUISITE: Math 2720 (prior to taking this course)
3 hours credit
MATH-3710 - GRAPH THEORY This course is an introduction to the ideas, methods, and applications of graph theory. Topics include graph connectivity, graph factors and factorizations, planar graphs, and colourings. Three lecture hours per week
PREREQUISITE: Math 2420 or Math 2720 (prior to taking this course)
3 hours credit
MATH-4020 - POINT-SET TOPOLOGY A first course in topology, covering some review of set theory; cardinal numbers; binary relations; metric spaces, convergence and continuity in metric spaces; topological spaces, bases, sub- spaces; continuity in general; homeomorphism; product spaces; separation axioms; compactness; connectedness. Three lecture hours per week
PREREQUISITE: Math 3510 (prior to taking this course)
3 hours credit
MATH-4520 - MEASURE THEORY AND INTEGRATION A first course in measure theory, covering measure as a generalization of length, outer measure, sigma-algebras, measurability, construction of measures, Lebesgue measure on the real line, measurable functions and the Lebesgue integral. Additional topics may include and convergence theorems, product measures and Fubini Theorem. Three lecture hours per week
PREREQUISITE: Math 3510 (prior to taking this course)
3 hours credit
MATH-4530 - FUNCTIONAL ANALYSIS This first course in functional analysis covers topics like: metric spaces, Banach spaces, function spaces, Hilbert spaces, generalized Fourier series and linear operators. Three lecture hours per week
PREREQUISITE: Math 2620 and Math 3510 (prior to taking this course)
3 hours credit
MATH-4620 - RING AND FIELD THEORY Introduction to ring and field theory, including: polynomial rings, matrix rings, ideals and homomorphisms, quotient rings, Chinese remainder theorem, Euclidean domains, principal ideal domains, unique factorization domains, introduction to module theory, basic theory of field extensions, splitting fields and algebraic closures, finite fields, introduction to Galois theory. Three lecture hours per week
PREREQUISITE: Math 3610 (prior to taking this course)
3 hours credit
MATH-4710 - PARTIAL DIFFERENTIAL EQUATIONS This course is an introduction to the theory and application of partial differential equations. Topics include: first-order equations and characteristic curves; classification of second-order equations as parabolic, hyperbolic or elliptic; Laplace, wave and diffusion equations, and their physical origins; solution using Fourier series; and separation of variables. Three lecture hours per week
PREREQUISITE: Math 2910 and Math 3010 (prior to taking this course)
3 hours credit
MATH-4720 - DYNAMICAL SYSTEMS This course is a study of the long-term qualitative behaviour of solutions of systems of differential or difference equations. Topics include: non-linear systems, linearization, numerical and graphical methods, equilibria, phase space, stability, bifurcations, strange attractors, and chaos. Applications to physics, biology and other sciences are studied. Three lecture hours per week
PREREQUISITE: Math 2610, Math 2910, and Math 3010 (prior to taking this course)
3 hours credit
MATH-ELEC1 - MATH ELECTIVE 1000 LEVEL
3 hours credit
MATH-ELEC2 - MATH ELECTIVE 2000 LEVEL
3 hours credit
MATH-ELEC3 - MATH ELECTIVE 3000 LEVEL
3 hours credit
MATH-ELEC4 - MATH ELECTIVE 4000 LEVEL
3 hours credit

Statistics (STAT) Courses

STAT-2210 - INTRODUCTORY STATISTICS I The main objective of this course is to introduce the basic concepts of descriptive statistics, statistical inference, and the use of statistical software such as MINITAB to students in any discipline. More time is spent on statistical inference than on descriptive statistics. Topics include frequency distributions, descriptive statistics, rules of probability, discrete and continuous probability distributions, random sampling and sampling distributions, confidence intervals, one- and two-tail tests of hypotheses, and correlation and linear regression. NOTE: Credit will not be allowed for Statistics 2210 if a student has received credit for any of the following courses: Business 2510, Education 4810, Psychology 2710 and Sociology 3320. Prerequisite: Grade XII academic Mathematics.
3 hours credit
STAT-2220 - INTRODUCTORY STATISTICS II The course builds upon the knowledge developed in Introductory Statistics I and introduces students to statistical techniques commonly used in research. Topics include linear regression and multiple linear regression, residual analysis, simple ANOVA models, categorical data analysis, simple sampling models, and common distributions (including binomial, Poisson, and exponential). Three lecture hours per week
PREREQUISITE: Statistics 2210 (prior to taking this course)
3 hours credit
STAT-3210 - PROBABILITY AND MATHEMATICAL STATISTICS I This course is an introduction to the theoretical basis of statistics for students who have completed Introductory Statistics. The study concentrates on the mathematical tools required to develop statistical methodology. Topics covered include: probability, continuous and discrete random variables, moment generating functions, multivariate probability distributions and functions of random variables. Three lecture hours per week
PREREQUISITE: Math 2910 and Stat 2220 or permission of the instructor (prior to taking this course)
3 hours credit
STAT-3220 - PROBABILITY AND MATHEMATICAL STATISTICS II This course builds on the mathematical foundation developed in Statistics 3210 and introduces the student to the theory of statistical inference. Topics covered include: sampling distributions and central limit theory, methods of estimation, hypothesis testing, least squares estimation of linear models, and an introduction to Bayesian inference. Three lecture hours per week
PREREQUISITE: Statistics 3210 (prior to taking this course)
3 hours credit
STAT-3240 - APPLIED REGRESSION ANALYSIS This course builds upon the basis of inference studied in Statistics 2210 and provides students with an advanced knowledge of regression techniques. Topics covered are simple and multiple linear regression techniques, matrix notation, the design matrix, model building techniques, residual analysis, and non-linear regression. Three lecture hours per week
PREREQUISITE: Statistics 2210 and Math 2610 (prior to taking this course)
3 hours credit
STAT-4110 - STATISTICAL SIMULATION This course introduces statistical simulation, and its use as a tool to investigate stochastic phenomena and statistical methods. Topics include the building and validation of stochastic simulation models useful in computing, operations research, engineering and science; related design and estimation problems; variance reduction; and the implementation and the analysis of the results. Three lecture hours per week
PREREQUISITE: Statistics 3220 (prior to taking this course)
3 hours credit
STAT-4240 - EXPERIMENTAL DESIGN This course builds upon the basis of inference studied in Statistics 2210 and Statistics 3240 to include statistical techniques commonly used in experimental studies. Students will study topics such as analysis of variance models, hypothesis testing in ANOVA models, randomization, and blocking techniques. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4280 - GENERALIZED LINEAR MODELS This course covers the basic theory, methodology and applications of generalized linear models. Topics include logistic regression, probit regression, binomial regression, Poisson regression, overdispersion, quasi-likelihood, and the exponential family. Three lecture hours per week
PREREQUISITE: Statistics 3220 and Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4330 - TIME SERIES I This course is an introduction to Time Series methods, including: stationary models, trends and seasonality, stochastic Time Series models, autoregressive and moving average processes and an introduction to Time Series forecasting. ARIMA models. Seasonal Time Series and Spectral Analysis are also covered. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4340 - TIME SERIES II This course includes topics from Time Series Econometrics, including Maximum Likelihood and Least Squares Estimation of ARIMA Models and GARCH Models, Wavelets and Financial Models. Non-stationary Time Series, multivariate Time Series and panel cointegration analysis are also covered. Three lecture hours per week
PREREQUISITE: Statistics 4330 (prior to taking this course)
3 hours credit
STAT-4410 - STOCHASTIC PROCESSES This course is an introduction to the branch of probability theory that deals with the analysis of systems that evolve over time. Topics include random walks, Markov chains, Poisson processes, continuous time Markov chains, birth and death processes, exponential models, and applications of Markov chains. Three lecture hours per week
PREREQUISITE: Statistics 3220 (prior to taking this course)
3 hours credit
STAT-4550 - DATA ANALYSIS AND INFERENCE This course is an introduction to data analysis with a focus on regression. Topics include: initial examination of data, correlation, and simple and multiple regression models using least squares. Inference for regression parameters, confidence and prediction intervals, diagnostics and remedial measures interactions and dummy variables, variable selection, least squares estimation and inference for non-linear regression will also be discussed. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4660 - DATA VISUALIZATION AND MINING This course introduces students to the statistical methods involved in visualization of high dimensional data, including interactive methods directed at exploration and assessment of structure and dependencies in data. Topics include methods for finding groups in data including cluster analysis, dimension reduction methods including multi-dimensional scaling, pattern recognition, and smoothing techniques. Three lecture hours per week
PREREQUISITE: Math 2620, Math 2910, and Statistics 3210 (prior to taking this course)
3 hours credit
STAT-4740 - MULTIVARIATE ANALYSIS This course deals with the statistics of observation and analysis of more than one output variable. Topics include estimation and hypothesis testing for multivariate normal data, principal component analysis and factor analysis, discriminant analysis, cluster analysis, and correspondence analysis. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-ELEC1 - STATISTICS ELECTIVE 1000 LEVEL
3 hours credit
STAT-ELEC2 - STATISTICS ELECTIVE 2000 LEVEL
3 hours credit
STAT-ELEC3 - STATISTICS ELECTIVE 3000 LEVEL
3 hours credit
STAT-ELEC4 - STATISTICS ELECTIVE 4000 LEVEL
3 hours credit

Computer Science (CS) Courses

CS-1210 - INTRODUCTION TO COMPUTER PROGR
3 hours credit
CS-1410 - INTRODUCTION TO COMPUTER PROGRAMMING FOR SCIENTISTS This course is an introduction to computer programming for non-computer science majors. Topics include problem-solving, algorithm design, data types, control structures, repetition, loops, nested structures, modular programming and arrays. Three lecture hours and 1.5 hours of laboratory session per week. NOTE: Credit will be allowed for only one of CS 1410 or Engineering 1320. As well, CS 1410 may not be taken concurrently with, or after, CS 1510. Prerequisite: Grade XII academic mathematics
PREREQUISITE: Computer Science 1410L (concurrent with taking this course)
3 hours credit
CS-1410L - Computer Science 1410 Lab
PREREQUISITE: Computer Science 1410 (concurrent with taking this course)
CS-1520L - Computer Science 1520 Programming Workshop
PREREQUISITE: Computer Science 1520 (concurrent with taking this course)
CS-1610 - DIGITAL SYSTEMS This course provides an introduction to digital systems, beginning with elementary components such as logic gates, from which are constructed components such as adders and comparators, and progressing to more complex systems such as programmable logic devices, memory and processor units. Students acquire skills in the design and analysis of combinational and sequential digital systems, CAD design and simulation tools for complex systems, and construction of digital systems based upon a modular methodology. Three lecture hours and a three-hour laboratory session per week
PREREQUISITE: Computer Science 1610L (concurrent with taking this course)
3 hours credit
CS-1610L - Computer Science 1610 Lab
PREREQUISITE: Computer Science 1610 (concurrent with taking this course)
CS-1910 - COMPUTER SCIENCE I This course is an introduction to computer programming and is designed for both Computer Science majors and non-majors. Emphasis is on problem solving and software development using a modern high level object-oriented language. Topics include: the programming process; language syntax and semantics; data types; expressions; input and output; conditionals; loops; arrays; functions/methods and text files. The course follos an "objects late" strategy, deferring in-depth discussions of object-orientated concepts to Computer Science 192. Prerequisite: Grade XII academic mathematics.
PREREQUISITE: Computer Science 1910L (concurrent with taking this course)
3 hours credit
CS-1910L - Computer Science 1910 Lab
PREREQUISITE: Computer Science 1910 (concurrent with taking this course)
CS-1920 - COMPUTER SCEINCE II This course continues the development of object-oriented programming. Topics include class design; inheritance; interfaces and polymorphism; collection classes; searching and sorting; recursion; exception handling; the Model-View-Controller pattern; and graphical user interfaces.
PREREQUISITE: Computer Science 1920L; (concurrent with taking this course)
3 hours credit
CS-1920L - Computer Sceince 1920 Lab
PREREQUISITE: Computer Sceince 1920; (concurrent with taking this course)
CS-2060 - WEB DEVELOPMENT AND PROGRAMMING In this course, students learn to create websites that involve server-side scripting and database operations. While one specific scripting language is used to acquire web development and programming skills, students are exposed to a spectrum of scripting languages, enabling them to easily adapt to others. Three hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2120 - MOBILE DEVICE DEVELOPMENT - iOS This course introduces the student to programming for mobile devices that use iOS. The course will present a study of the architecture, operating system, and programming for these devices. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2130 - MOBILE DEVICE DEVELOPMENT - ANDROID This course introduces the student to programming for mobile devices that use the Android platform. The course will present a study of the architecture, operating system and programming language of these devices. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or CS-1920 (prior to taking this course)
3 hours credit
CS-2520 - COMPUTER ORGANIZATION AND ARCHITECTURE This course provides a basic understanding of the organization and architecture of modern computer systems. It examines the function and design of major hardware components both from a designer's perspective and through assembly language programming. Topics include components and their interconnection, internal/external memory, input/output subsystems, processors, computer arithmetic, instruction sets, addressing modes, and pipelining. Three hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2610 - DATA STRUCTURES AND ALGORITHMS This course continues the study of data structures, recursive algorithms, searching and sorting techniques, and general strategies for problem solving. It also introduces complexity analysis and complexity classes. Three lecture hours per week
PREREQUISITE: Computer Science 1520 and six credit hours of Mathematics (prior to taking this course)
3 hours credit
CS-2620 - COMPARATIVE PROGRAMMING LANGUAGES This course examines the principal features of major types of programming languages, including procedural, logical, functional and object-oriented languages. Features include parameter-passing mechanisms, control structures, scope, and binding rules. Each language type is illustrated by considering a specific language. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-2710 - PRACTICAL EMBEDDED SYSTEMS This course introduces students to the concept of embedded systems architectures, the interconnection of sensors and actuators to such systems, and the usage of such platforms for data acquisition and control of automated systems. Popular microcontroller units and system-on-chip platforms will be examined. Three lecture hours per week
PREREQUISITE: Computer Science 1210 or Computer Science 1410 or Computer Science 1510 or Engineering 1310 or CS-1920 (prior to taking this course)
3 hours credit
CS-2820 - PROGRAMMING PRACTICES This course introduces the student to development in the Unix/Linux environment. Topics include development tools, shell programming, common utility programs, processes, file/directory management, IDEs, testing/debugging, version control, and an introduction to software engineering. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 permission of the instructor (based on completion of CS 1510 with first class standing) (prior to taking this course)
3 hours credit
CS-2910 - COMPUTER SCIENCE III This is the third course in the Computer Science programming sequence. It covers more advanced programming concepts in an object oriented language. It also serves as an introduction to data structures and software engineering. Topics included: the programming toolchain; threads; class generics; lists, stacks, queues and binary trees; streams and binary I/O, object serialization, networking (sockets and web interface); introduction to software engineering; relational database connectivity; and XML parsing.
PREREQUISITE: Computer Science 1920 and 6 Math credits (prior to taking this course)
3 hours credit
CS-2910L - Computer Science 2910 Lab
PREREQUISITE: Computer Science 2910; (concurrent with taking this course)
CS-2920 - DATA STRUCTURES AND ALGORITHMS This course continues the study of data structures, recursive algorithms, searching and sorting techniques, and general strategies for problem solving. It also introduces complexity analysis and complexity classes. Three lecture hours per week
PREREQUISITE: Computer Science 2910 and 6 Math credits (prior to taking this course)
3 hours credit
CS-2920L - Computer Science 2920 Lab
PREREQUISITE: Computer Science 2920; (concurrent with taking this course)
CS-3110 - VIDEO GAME DESIGN This course focuses on the process from initial idea to final design of a video game. Students will craft a game document from an original concept of their own creation and create a prototype of the game based on that document. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3210 - HUMAN-COMPUTER INTERFACE DESIGN This course is an introduction to the design and evaluation of software interfaces and webpages. The course focuses on user-centered design and includes topics such as user analysis and modelling, iterative prototyping, usability testing, designing for the web, internationalization and localization. Three hours per week
PREREQUISITE: Computer Science 1520 (prior to taking this course)
3 hours credit
CS-3220 - INTRODUCTION TO BIOINFORMATICS This course is an introduction to bioinformatics, with a focus on a practical guide to the analysis of data on genes and proteins. It familiarizes students with the tools and principles of contemporary bioinformatics. Students acquire a working knowledge of a variety of publicly available data and computational tools important in bioinformatics, and a grasp of the underlying principles enabling them to evaluate and use novel techniques as they arise in the future. Cross-listed with Biology, Pathology/Microbiology, Human Biology (cf. Biology 3220, VPM 8850, HB 8850). Three lecture hours and a one-hour laboratory session per week. NOTE: No student can be awarded more than one course credit among HB 8850, VPM 8850, CS 3220 and BIO 3220.
PREREQUISITE: Computer Science 3220L (concurrent with taking this course)
3 hours credit
CS-3220L - Computer Science 3220 Lab
PREREQUISITE: Computer Science 3220 (concurrent with taking this course)
CS-3320 - THEORY OF COMPUTING
3 hours credit
CS-3420 - COMPUTER COMMUNICATIONS This course introduces the basic principles of modern computer communication: protocols, architectures and standards. Topics include layered architectures, data transmission, error and flow control, medium access, routing, congestion control and common internet application protocols. Three lecture hours per week
PREREQUISITE: Computer Science 2520 and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-3520 - OPERATING SYSTEMS This course introduces the student to the major concepts of modern operating systems. Topics covered include: process management, memory management, file systems, device management and security. Three lecture hours per week
PREREQUISITE: Computer Science 2520, Computer Science 2610, and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-3610 - ANALYSIS AND DESIGN OF ALGORITHMS This course, which introduces the study of algorithm design and measures of efficiency, is a continuation of CS 2610. Topics include algorithm complexity and analysis; techniques such as divide and conquer, greedy and dynamic programming; searching and sorting algorithms; graph algorithms; text processing; efficient algorithms for several common computer science problems and NP-completeness. Three lecture hours per week
PREREQUISITE: Computer Science 2610 and Math 2420 (prior to taking this course)
3 hours credit
CS-3620 - SOFTWARE DESIGN AND ARCHITECTURE This course examines the principles and best practices in object-oriented (OO) software design. Topics include a review of foundational OO concepts, OO design principles, classic design patterns, and software architectures. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3710 - DATABASE SYSTEMS This course introduces the fundamental concepts necessary for the design, use and implementation of database systems. Topics discussed include logical and physical organization of data, database models, design theory, data definition and manipulation languages, constraints, views, and embedding database languages in general programming languages. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3840 - TECHNOLOGY MANAGEMENT & ENTREPRENEURSHIP This course provides an overview on how to start and sustain a technology-oriented company. Topics discussed will include the role of technology in society, intellectual property, patents, business plans, financial planning, sources of capital, business structure, liability, tax implications, sales, marketing, operational and human resource management. This course will be taught using problem-based and experiential learning strategies with involvement from real life entrepreneurs as motivators and facilitators. (Cross-listed with Engineering 4430. Three lecture hours per week.
PREREQUISITE: Computer Science 2520, Computer Science 2620, and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-4060 - CLOUD COMPUTING This course examines: the critical technology trends that are enabling cloud computing, the architecture and the design of existing deployments, the services and the applications they offer, and the challenges that need to be addressed to help cloud computing to reach its full potential. The format of this course will be a mix of lectures, seminar-style discussions, and student presentations. Three lecture hours per week
PREREQUISITE: Computer Science 2060 (prior to taking this course)
3 hours credit
CS-4110 - ARTIFICIAL INTELLIGENCE AND AUTOMATED REASONING This course introduces general problem-solving methods associated with automated reasoning and simulated intelligence. Topics include problem abstraction, state space heuristic search theory, pathfinding, flocking behaviour, knowledge representation, propositional logic, reasoning with uncertainty, machine learning and connectionism. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-4120 - MACHINE LEARNING AND DATA MINING Machine learning is the study of mechanisms for acquiring knowledge from large data sets. This course examines techniques for detecting patterns in sets of uncategorized data. Supervised and unsupervised learning techniques are studied, with particular application to real-world data. Three lecture hours per week
PREREQUISITE: Computer Science 3710 and Statistics 2210 (prior to taking this course)
3 hours credit
CS-4230 - PHYSICS OF GAMING
3 hours credit
CS-4350 - COMPUTER GRAPHICS PROGRAMMING This course introduces the student to the principles and tools of applied graphics programming including graphical systems, input and interaction, object modeling, transformations, hidden surface removal, and shading and lighting models. Languages, graphics libraries and toolkits, and video game engines are introduced, as well as relevant graphics standards. Three lecture hours per week
PREREQUISITE: Computer Science 2620 and Math 2610 (prior to taking this course)
3 hours credit
CS-4360 - ADVANCED COMPUTER GRAPHICS PROGRAMMING This course builds on the computer graphics programming concepts introduced in CS 4350. Students are given a deeper understanding of the components of the 3D graphics pipeline, and how they are used in modern graphical applications. Topics include advanced texture mapping, practical uses of vertex and pixel shaders, screen post-processing, particle systems, and graphics engine design. Three lecture hours per week
PREREQUISITE: Computer Science 4350 (prior to taking this course)
3 hours credit
CS-4440 - DATA SCIENCE Data science is an interdisciplinary and emerging field where techniques from several areas are used to solve problems using data. This course provides an overview and hands-on training in data science, where students will learn to combine tools and techniques from computer science, statistics, data visualization and the social sciences. The course will focus on: 1) the process of moving from data collection to product, 2) tools for preparing, manipulating and analyzing data sets (big and small), 3) statistical modelling and machine learning, and 4) real world challenges. Three lecture hours per week
PREREQUISITE: Computer Science 3710 and Statistics 2210 (prior to taking this course)
3 hours credit
CS-4610 - WIRELESS SENSOR NETWORKS This course is an introduction to Wireless Sensor Networks. It includes the following topics: single-node architecture, wireless sensor network architecture, physical layer, MAC protocols, link-layer protocols, naming and addressing, time synchronization, localization and positioning, topology control, routing protocols, transport layer, and quality of service. Three lecture hours per week
PREREQUISITE: Computer Science 2520 and Computer Science 2610 (prior to taking this course)
3 hours credit
CS-4650 - VIDEO-GAME ARCHITECTURE This programming-driven course aims to explore the various systems that comprise a typical video-game project, including event systems, state machines, rendering, scripting and AI programming. Students will implement these components throughout the course with the end goal of building a small game. Three lectures hours per week
PREREQUISITE: Computer Science 4360
3 hours credit
CS-4720 - COMPILER DESIGN This is a first course in compiler design. The course covers: compilation phases, lexical analysis, parsing, scope rules, block structure, symbol tables, run-time heap and stack management, code generation, pre-processing, compiler-compilers, and translation systems. Three lecture hours per week
PREREQUISITE: MCS 3320 (prior to taking this course)
3 hours credit
CS-4810 - SOFTWARE ENGINEERING This course emphasizes the theory, methods and tools employed in developing medium to large-scale software which is usable, efficient, maintainable, and dependable. Project management is a major focus. Topics include traditional and agile process models, project costing, scheduling, team organization and management, requirements modelling/specification, software design, software verification and testing, and re-engineering. Three lecture hours per week. Restriction: Student must have fourth year standing in Computer Science
3 hours credit
CS-4820 - SOFTWARE SYSTEMS DEVELOPMENT PROJECT In this course, students propose, complete and present a significant software project in a group setting using the system development skills learned in CS 4810. The course applies object-oriented design principles through the use of UML. Students are encouraged to select (with the consent of the instructor) a project with a real-world client. One lecture hour per week plus significant project time
PREREQUISITE: Computer Science 4810 (May be taken concurrently in exceptional circumstances) (prior to taking this course)
3 hours credit
CS-4830 - VIDEO GAME PROGRAMMING PROJECT In this course, students work as a group to develop a single design into a fully functioning video game. This course applies the project management skills learned in CS 4810 to the development of a professional quality video game based upon a single design and prototype emerging from CS 3110. One lecture hour per week plus significant project time. Semester hours of credit: 6
PREREQUISITE: Computer Science 3110, Computer Science 4810 and enrolment in the Computer Science with Video Game Programming major. (prior to taking this course)
6 hours credit
CS-4840 - PROTOTYPE SYSTEMS DEVELOPMENT This course is for student teams who wish to develop an early prototype of a product which they hope to pitch to an external start-up accelerator program post-graduation. Student teams may be inter-disciplinary, but students must register for this course (or its equivalent) within their home school/department. Entry into the course is dependent upon a pitch for the product being judged as economically viable by a team of project mentors. Pitches are made at the conclusion of CS 3840. One lecture hour per week plus significant project time. Semester hours of credit: 6
PREREQUISITE: Computer Science 3840 and permission of the instructor (prior to taking this course)
6 hours credit
CS-ELEC - COMPUTER SCIENCE ELECTIVE
3 hours credit
CS-ELEC1 - COMP. SCI. ELECTIVE 1000 LEVEL
3 hours credit
CS-ELEC2 - COMP. SCI. ELECTIVE 2000 LEVEL
3 hours credit
CS-ELEC3 - COMP SCI ELECTIVE
3 hours credit
CS-ELEC4 - COMP SCI ELECTIVE 4000 LEVEL
3 hours credit

Applied Mathematical Sciences (AMS) Courses

AMS-2160 - MATHEMATICS OF FINANCE This first course in the mathematics of finance includes topics such as measurement of interest; annuities and perpetuities; amortization and sinking funds; rates of return; bonds and related securities; life insurance. Three lecture hours a week
PREREQUISITE: Math 1910 (prior to taking this course)
3 hours credit
AMS-2160L - Mathematics of Finance Lab
PREREQUISITE: AMS 2160 (concurrent with taking this course)
AMS-2400 - FINANCIAL MATHEMATICS & INVESTMENTS Advanced topics of Theory of Interest as initially covered in AMS 2160 including time value of money, annuities, loans, bonds, general cash flows, portfolios and immunization concepts, as well as an introduction to capital markets, analysis of equity and fixed income investments, and an introduction to derivative securities including futures, forwards, swaps and options. Three lecture hours plus a two hour lab per week
PREREQUISITE: AMS 2400L (concurrent with taking this course)
3 hours credit
AMS-2400L - Financial Mathematics and Investments Lab
PREREQUISITE: AMS 2400 (concurrent with taking this course)
AMS-2400T - AMS 2400 TUTORIAL
PREREQUISITE: AMS-2400; (concurrent with taking this course)
AMS-2410 - FINANCIAL ECONOMICS I Introduction to mathematical techniques used to price and hedge derivative securities in modern finance. Modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes. Applications of derivatives in practice will also be discussed. Three lecture hours a week
PREREQUISITE: AMS 2410 Lab (concurrent with taking this course)
3 hours credit
AMS-2410L - Financial Economics Lab I
PREREQUISITE: AMS 2410 (concurrent with taking this course)
AMS-2510 - ACTUARIAL SCIENCE I This course will explore the future lifetime random variable, probability and survival functions, force of mortality; complete and curtate expectation of life, and Makeham and Gompertz mortality laws. Other topics will include: Life tables, characteristics of population and insurance life tables, selection, and fractional age assumptions. Life insurance payments and annuity payments: Present value random variables; expected present values; higher moments; actuarial notation, annual, 1/mthly and continuous cases, relationships between insurance and annuity functions. Premiums, expense loadings, present value of future loss random variables and distribution, net and gross cases, the equivalence principle and portfolio percentile principle will also be discussed. Three lecture hours a week
PREREQUISITE: AMS-2510L (concurrent with taking this course)
3 hours credit
AMS-2510L - Actuarial Science Lab 1
PREREQUISITE: AMS 2510 (concurrent with taking this course)
AMS-2860 - ACTUARIAL MATHEMATICS LAB I This lab features problem-solving sessions for the professional examination on financial mathematics of the Society of Actuaries and the Casualty Actuarial Society. Semester hours of credit: 1
PREREQUISITE: AMS 2160 (prior to taking this course)
3 hours credit
AMS-2940 - OPTIMIZATION An introduction to the methods and applications of linear programming. Topics include linear programming formulations, the simplex method, duality and sensitivity analysis, and integer programming basics. Applications to transportation, resource allocation and scheduling problems will be examined. Software will be used to illustrate topics and applications. Three lecture hours per week
PREREQUISITE: MATH 2610 (prior to taking this course)
3 hours credit
AMS-3160 - GAME THEORY The course covers the fundamentals of game theory and its applications to the modeling of competition and cooperation in business, economics, biology and society. It will include two-person games in strategic form and Nash equilibria, extensive form games, including multi-stage games, coalition games and the core Bayesian games, mechanism design and auctions. PREREQUISITES: Math 192, Math 242 and Stat 222 Three lecture hours per week
PREREQUISITE: Math 1920, Math 2420 and Statistics 2220 (prior to taking this course)
3 hours credit
AMS-3310 - ADVANCED CORPORATE FINANCE FOR ACTUARIES This course covers various advanced topics in corporate finance, with emphasis on theories of corporate incentives and asymmetric information. Illustrative applications using cases are provided. Topics include: capital budgeting, real options, investment decision using Markowitz and utility theory, the Capital Asset Pricing Model, Arbitrage Pricing Theory, market efficiency and capital structure and dividend policy. Other topics may include time value of money, capital budgeting, cost of capital, security issuance, capital structure, payout policy and dividends, short-term finance, and risk management. Where suitable, topics are treated from a mathematical and quantitative perspective. Three lecture hours per week
PREREQUISITE: AMS 2400 and BUS 2310 (prior to taking this course)
3 hours credit
AMS-3410 - FINANCIAL ECONOMICS II This course will discuss advanced mathematical techniques used to price and hedge derivative securities in modern finance. Topics include: modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes. Students will also have the opportunity to apply these derivatives in practice. Three lecture hours per week
PREREQUISITE: AMS 3410L (concurrent with taking this course)
3 hours credit
AMS-3410L - Financial Economics II Lab
PREREQUISITE: AMS 3410 (concurrent with taking this course)
AMS-3510 - ACTUARIAL SCIENCE II This course will discuss: policy values, annual, 1/mthly and continuous cases, Thiele's equation, policy alterations, modified policies and multiple state models. Other topics will include applications in life contingencies, assumptions, Kolmogorov equations, premiums, policy values, multiple decrement models, Joint Life Models, Valuation of insurance benefits on joint lives, and dependent and independent cases. Three lecture hours per week
PREREQUISITE: AMS-3510L (concurrent with taking this course)
3 hours credit
AMS-3510L - Actuarial Science II Lab
PREREQUISITE: AMS 3510 (concurrent with taking this course)
AMS-3730 - ADVANCED INSURANCE AND ACTUARIAL PRACTICES This course is a study of cash flow projection methods for pricing, reserving and profit testing. Topics include: deterministic, stochastic and stress testing; pricing and risk management of embedded options in insurance products; mortality and maturity guarantees for equity-linked life insurance. Three lecture hours per week
PREREQUISITE: AMS 3510 (prior to taking this course)
3 hours credit
AMS-3770 - COMBINATORIAL OPTIMIZATION In this course, various algorithms will be considered, including minimum spanning tree, shortest path, maximum flow, and maximum matching. The links with linear and integer programming will also be considered, with particular attention to duality. Three lecture hours per week
PREREQUISITE: MATH 2420 and AMS 2940 (prior to taking this course)
3 hours credit
AMS-3910 - MATHEMATICAL MODELLING This course studies the process of mathematical modeling, namely, formulating a "real-world" problem in mathematical terms, solving the resulting mathematical problem, and interpreting the solution. Major topics include the modeling of optimization problems (using the techniques of linear programming), and deterministic and probabilistic dynamical processes (with models formulated as differential and difference equations). Applications are taken from science, business and other areas, according to class interest. Three lecture hours per week
PREREQUISITE: A statistics course (prior to taking this course)
3 hours credit
AMS-4080 - FINANCIAL MATHEMATICS II This course explores calculus in a stochastic environment. Topics include: random functions, derivative, chain rule, integral, integration by parts, partial derivatives, pricing forwards and options. Ito's lemma and financial applications, Hull-White, Artzner-Heath, and Brennan-Schwartz models Martingales, pricing methodology, and risk-neutral probability will also be discussed. Three lecture hours per week
PREREQUISITE: MATH 2610 and AMS 3410 (prior to taking this course)
3 hours credit
AMS-4090 - FINANCIAL MATHEMATICS III This course discusses forming risk-free portfolios, the Black-Scholes partial differential equation, constant dividend case, exotic options, drift adjustment, and equivalent martingale measures. Topics also include: Cox-Ross-Rubinstein, Merton and Vasicek's models, stochastic optimization, Hamilton-Jacobi-Bellman equation, and application to American options. Three lecture hours per week
PREREQUISITE: AMS 4080 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4540 - LOSS MODELS I This course explores models for loss severity, parametric models, effect of policy modifications, and tail behaviour. Topics also include: models for loss frequency: (a, b, 0), (a, b, 1), mixed Poisson models; compound Poisson models, Aggregate claims models: moments and moment generating function: recursion and Classical ruin theory. Three lecture hours per week
PREREQUISITE: AMS 3510 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4550 - LOSS MODELS II This course is a study of the mathematics of survival models and includes some examples of parametric survival models. Topics include: tabular survival models, estimates from complete and incomplete data samples, parametric survival models, and determining the optimal parameters. Maximum likelihood estimators, derivation and properties, product limit estimators, Kaplan-Meier and Nelson-Aalen, credibility theory: limited fluctuation; Bayesian; Buhlmann; Buhlmann-Straub; empirical Bayes parameter estimation; statistical inference for loss models; maximum likelihood estimation; the effect of policy modifications; and model selection will also be discussed. Three lecture hours per week
PREREQUISITE: AMS 4540 (prior to taking this course)
3 hours credit
AMS-4580 - CREDIBILITY THEORY This course is a credibility approach to inference for heterogeneous data; classical, regression and Bayesian models; with illustrations from insurance data. Three lecture hours per week
PREREQUISITE: AMS 3510 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4680 - NONLINEAR OPTIMIZATION This course is a study of unconstrained optimization, optimality conditions (necessary, sufficient and Karush-Kuhn-Tucker), penalty functions, convex functions, and convex programming. Three lecture hours per week
PREREQUISITE: MATH 2910 and AMS 2940 (prior to taking this course)
3 hours credit
AMS-4780 - QUANTITATIVE RISK MANAGEMENT This course is an introduction to financial risk management. Topics include: risk measures, modeling for multivariate distributions and copulas, market, credit and operational risk. Advanced topics in quantitative risk management will also be discussed. Three lecture hours per week
PREREQUISITE: AMS 3310 (prior to taking this course)
3 hours credit
AMS-ELEC1 - APP. MATH ELECTIVE 1000 LEVEL
3 hours credit
AMS-ELEC2 - APP. MATH ELECTIVE 2000 LEVEL
3 hours credit
AMS-ELEC3 - APP. MATH ELECTIVE 3000 LEVEL
3 hours credit
AMS-ELEC4 - APP. MATH ELECTIVE 4000 LEVEL
3 hours credit

Mathematical and Computational Sciences (MCS) Courses

MCS-2010 - MAPLE TECHNOLOGY LAB An introduction to the software package MAPLE. Topics include the basic functions and commands, mathematical problem solving using MAPLE, and programming in the internal MAPLE language. Two lab hours per week for 6 weeks. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Math 1920 (prior to taking this course)
1 hour credit
MCS-2020 - MATLAB TECHNOLOGY LAB An introduction to the software package Matlab. Topics include the basic functions and commands, programming and problem-solving using Matlab. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Math 2610 (prior to taking this course)
1 hour credit
MCS-2030 - R TECHNOLOGY LAB An introduction to the software package R. Topics include the basic functions and commands, programming and problem-solving using R. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Statistics 2220 (prior to taking this course)
1 hour credit
MCS-2040 - VISUAL BASIC IN EXCEL TECHNOLOGY LAB An introduction to the software package Excel and Visual Basic in the Excel environment. Topics include the basic functions and commands, programming and problem-solving using Excel and Visual Basic. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and AMS 2400 (prior to taking this course)
1 hour credit
MCS-2050 - GGY AXIS TECHNOLOGY LAB An introduction to the software package GGY AXIS. Topics include the basic functions and commands, programming and problem-solving using GGY AXIS. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and AMS 2510 (prior to taking this course)
1 hour credit
MCS-2840 - CO-OP CAREER SKILLS I This course offers introductory career skills training to prepare co-op students for their first work term. Students are assessed on a pass/fail basis. Cross-listed with Business (cf. Business 2920) Semester hours of credit: 0 Restriction: Student must be admitted into the Mathematical and Computational Sciences Co-operative Education Program
MCS-2850 - CO-OP WORK TERM I This course is a co-op students' first work term. A work term report related to a technical problem/issue within the organization where the student is working is required. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 2840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-3050 - TUTORING IN MATHEMATICAL AND COMPUTATIONAL SCIENCES Students are introduced to techniques for facilitating learning in the Mathematical and Computational Sciences, and then put these techniques into practice by mediating student group learning either in introductory Mathematical and Computational Sciences courses, Mathematical and Computational Science Help Centre or in outreach programs to High Schools. Semester hours of credit: 1
PREREQUISITE: At least 36 credit hours completed in courses in the School of Mathematical and Computational Sciences (prior to taking this course)
1 hour credit
MCS-3320 - THEORY OF COMPUTING This course introduces automata theory, formal languages and computability. Topics include: finite automata; regular expressions; regular, context-free, and context-sensitive languages; computability models; algorithmic decidable and undecidable problems. Three lecture hours per week
PREREQUISITE: Computer Science 2610 and Math 2420 (prior to taking this course)
3 hours credit
MCS-3500 - QUANTUM INFORMATION Introduction to quantum information science; the field of studying, storing, processing and communicating information using quantum systems. Topic include quantum mechanics for Qubit Systems, foundations of Quantum Computing, algorithms, communication and cryptography. Three lecture hours per week.
PREREQUISITE: Math 2620 (prior to taking this course)
3 hours credit
MCS-3840 - CO-OP CAREER SKILLS II This course offers career skills training to strengthen co-op students' readiness for their second work term. Students are assessed on a pass/fail basis. Cross-listed with Business (cf. Business 3920) Semester hours of credit: 0
PREREQUISITE: MCS 2850 (prior to taking this course)
MCS-3850 - CO-OP WORK TERM II This course is a co-op students' second work term. Students will submit a report summarizing their work term achievements. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 3840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-3920 - NUMERICAL ANALYSIS Approximate solution of equations, various interpolative or iterative methods, especially Newton's; convergence tests and rates of convergence; roundoff and truncation errors; propagation of error in calculations; interpolating polynomials; Gauss-Jordan and other methods for simultaneous linear equations; inversion of matrices; determinants and eigenvalues; simultaneous nonlinear equations; evaluation of definite integrals; approximate derivatives; initial-value ordinary differential equations; least-squares curve fitting. Three lecture hours per week
PREREQUISITE: Math 3010 and Computer Science 1510 or equivalent (prior to taking this course)
3 hours credit
MCS-3950 - This course provides students with an opportunity to pursue special topics in Mathematical and Computational Science. Content varies from year to year. Three lecture hours per week. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-4210 - PROFESSIONAL COMMUNICATION AND PRACTICE This course aims to build students' oral and written communications skills, and to prepare them for a professional environment. Using examples from their discipline, students will focus on such aspects as description of processes, presentation of data, extended abstracts, correct use of terminology, and sensitivity to language and tone. Discussions of topics relevant to the professional Mathematical and Computational Scientist are also a key part of the course. Three hours per week
PREREQUISITE: At least 36 credit hours completed in the School of Mathematical and Computational Sciences (prior to taking this course)
3 hours credit
MCS-4420 - CRYPTOGRAPHY AND CODES This course is a study of classic and modern methods of encryption, applications to public-key ciphers, random number generators, attacks on encryption systems, error correcting codes; and computational number theory. Three lecture hours per week
PREREQUISITE: Math 3420 (prior to taking this course)
3 hours credit
MCS-4840 - CO-OP CAREER SKILLS III This course offers career skills training to strengthen co-op students' readiness for their third work term. Students are assessed on a pass/fail basis. Cross-listed with Business 4920 and Physics 4840 Semester hours of credit: 0
PREREQUISITE: MCS 3850 (prior to taking this course)
MCS-4850 - CO-OP WORK TERM III This course is a co-op students' third work term. Students will submit a report summarizing their work term achievements. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 4840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-4860 - CO-OP WORK TERM IV This optional work term is only available to co-op students in the School of Mathematical and Computational Sciences, who elect for a fourth work term. The goal is to add further value for the student, integrating classroom theory with professional skills acquired during the work term. Semester hours of credit: 0
PREREQUISITE: MCS 4850 (prior to taking this course)
MCS-4900 - HONOURS PROJECT This course is intended to give research experience to students planning to pursue graduate studies in an area of Mathematical and Computational Sciences, or planning a career where research experience would be an asset. It provides students with the opportunity to do an independent research project on Mathematical or Computational Sciences topic, under the supervision of a faculty member. Some or all of the work may be done during the summer months. Semester hours of credit: 6 Restriction: Student must be accepted to an Honours program in the School of Mathematical and Computational Sciences
6 hours credit
MCS-4910 - DIRECTED STUDIES IN MATHEMATICAL AND COMPUTATIONAL SCIENCES These courses are designed and recommended for students in the Mathematical and Computational Sciences to encourage independent initiative and study. Reading and research will be conducted in one or more specialized areas. (See Academic Regulation 9 for Regulations Governing Directed Studies.) Three semester hours of credit. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-4950 - ADVANCED TOPICS IN MATHEMATICAL AND COMPUTATIONAL SCIENCES This course provides students with an opportunity to pursue advanced topics in Mathematical and Computational Sciences. Content varies from year to year but is always at a fourth-year level. Prospective students should contact the School of Mathematical and Computational Sciences for a more detailed description of any particular year's offering. Three lecture hours per week. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-ELEC1 - MCS ELECTIVE 1000 LEVEL
3 hours credit
MCS-ELEC2 - MCS ELECTIVE 2000 LEVEL
3 hours credit
MCS-ELEC3 - MCS ELECTIVE 3000 LEVEL
3 hours credit
MCS-ELEC4 - MCS ELECTIVE 4000 LEVEL
3 hours credit

Information Technology (IT) Courses

IT-1210 - INTRODUCTION TO COM PROGRAM
3 hours credit
IT-1320 - This course will address traditional storytelling and the challenges of interactive narrative. Students will develop a solid understanding of traditional narrative theory as well as experimental approaches to storytelling in literature, theatre and film with relevance to game development. Three lecture hours per week
3 hours credit
IT-3710 - This course is an introduction to relational database concepts and design for non-computer science majors. Topics include the logical and physical organization of data, database models, design theory, data definition and manipulation languages, constraints, views, database security, data warehousing and data mining.
3 hours credit
IT-ELEC1 - INFO TECH ELECTIVE 1000 LEVEL
3 hours credit
IT-ELEC2 - INFO TECH ELECTIVE 2000 LEVEL
3 hours credit
IT-ELEC3 - INFO TECH ELECTIVE 3000 LEVEL
3 hours credit
IT-ELEC4 - INFO TECH ELECTIVE 4000 LEVEL
3 hours credit
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The School of Mathematical and Computational Sciences is located in Cass Science Hall.
Overview

The School of Mathematical and Computational Sciences (SMCS) is built on a strong foundation of core Mathematics and Computer Science programs that have existed at UPEI for many years. The SMCS is unique in Atlantic Canada for offering a comprehensive suite of majors in the quantitative disciplines.

Mathematical and computational sciences are experiencing a “boom”, as many industries and sectors need people with the skills to manage, analyze, and extract useful information from data. This is what mathematicians, statisticians, and computer scientists are trained to do. Analytics (sometimes called “data science”) is at the intersection of mathematics, statistics, and computer science, and is the hottest area of job growth right now.

We offer the only complete actuarial degree in Atlantic Canada. The unemployment rate for actuaries in Canada is 0%, and the mid-career average salary is near $100,000. When our program is accredited by the Canadian Institute of Actuaries, UPEI will be one of only 12 universities in Canada with an accredited program in actuarial science.

Visit the "Programs" tab to learn about our degrees.  

Programs

The School of Mathematical and Computational Sciences offers degrees in:


Course code prefixes

In the School of Mathematical and Computational Sciences, there are five course prefixes:

  • MATH – for Mathematics courses
  • STAT – for Statistics courses
  • CS – for Computer Science courses
  • AMS – for Applied Mathematical Sciences courses (mainly Actuarial Science and Financial Mathematics)
  • MCS – for common or interdisciplinary courses in Mathematical and Computational Science

Common requirements across all degree programs in the School of Mathematical and Computational Sciences

COMMON CORE

All degree programs in the School of Mathematical and Computational Sciences are built on a common core of courses that should be completed in the first two years of study. This common core consists of the following courses:

Course Course name Credits
MATH 1910 Single Variable Calculus I 4
MATH 1920 Single Variable Calculus II 4
MATH 2610 Linear Algebra I 3
STAT 2210 Introductory Statistics 3
CS 1910 Computer Science I 3
CS 1920 Computer Science II 3

One of:
UPEI 1010
UPEI 1020
UPEI 1030


Writing Studies
Inquiry Studies
University Studies

3
Total Semester Hours of Credit   23

COMMON BREADTH REQUIREMENT

Students must take at least 15 semester hours of credit in courses outside the School of Mathematical and Computational Sciences (excluding one of the UPEI courses listed above), and of these 15 semester hours of credit, at least 6 must be from Biology, Chemistry or Physics and at least 6 must be from outside the Faculty of Science.

COMMON ADVANCED COURSES

Students in all degree programs in the School of Mathematical and Computational Sciences must complete MCS 4210 Professional Communication and Practice (writing-intensive) and MCS 3050 Tutoring in Mathematical and Computational Sciences. 


REQUIREMENTS FOR A MAJOR IN MATHEMATICS

Mathematics is the study of quantity, structure and space. While mathematics is important in understanding and influencing the physical world around us, mathematics can also be curiosity-driven and enjoyed without the requirement of a particular application. The Bachelor of Science with a major in Mathematics provides students with a solid foundation in both pure and applied mathematics, preparing them for graduate studies and professional programs. Students interested in graduate studies in mathematics should consider the Bachelor of Science with honours in Mathematics.

The Major in Mathematics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910- Multivariable and Vector Calculus 4

MATH 2620 - Linear Algebra II

3
MATH 2720 - Mathematical Reasoning  3

At least one of:  MCS 2010 - MAPLE Technology Lab or  MCS 2020  - Matlab Technology Lab

1
MATH 2420 - Combinatorics I   3
STAT 2220 - Introductory Statistics II 3
MATH 3510 - Real Analysis       3
MATH 3610 - Group Theory     3

At least one of : MATH 3010 - Differential Equations, STAT  3210 - Probability and Mathematical Statistics I or  MATH 3310 - Complex Variables

3

Five electives in the Mathematical and Computational Sciences (at the 2000 level or higher with at least two at the 3000 level or higher)

15
MCS 3050 - Tutoring in Mathematical and Computational Sciences    1
MCS 4210 - Professional Communication and Practice 3
Additional general electives                         52
Total Semester Hours of Credit       120

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REQUIREMENTS FOR A MAJOR IN STATISTICS

Statistics is the practice of collecting and analyzing numerical data, and inferring properties of the whole from a representative sample. The Bachelor of Science with a major in Statistics provides students with the solid foundation in both statistical theory and applied statistics necessary to become a statistician or proceed to more specialized statistical study at the graduate level. Students interested in continuing to work in statistics research should consider the Bachelor of Science with honours in Statistics.

The Major in Statistics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3
MCS 2030 - R Technology Lab 1
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I                 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4550 - Data Analysis and Inference 3
STAT 4240 - Experimental Design 3
STAT 4330 - Time Series I       3
STAT 4110 - Statistical Simulation 3
STAT 4410 - Stochastic Processes 3

Two electives in the Mathematical and Computational Sciences (at the 2000 level or higher)           

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit       120

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REQUIREMENTS FOR A MAJOR IN COMPUTER SCIENCE

Computer Science is a key enabler for innovation and discovery in most fields. It encompasses both theory and practice; theoretical ideas about how information is represented and processed, and practical techniques for creating new software. The School offers options such as co-operative education, a specialization in video game programming, and an Honours degree. Employment prospects are among the highest of any field. Honours graduates are well positioned to pursue graduate studies.

The Major in Computer Science requires a total of 120 semester hours of credit, as described below.  

  Credits
The Common Core 23
CS 1610 - Digital Systems 3
CS 2520 - Computer Organization and Architecture 3
CS 2610 -  Data Structures and Algorithms 3
CS 2620 - Comparative Programming Languages 3
CS 2820 - Programming Practices 3
MATH 2420 - Combinatorics I 3
MCS 3320 - Theory of Computing 3
CS 3420 - Computer Communications         3
CS 3520 - Operating Systems 3
CS 3610 - Analysis and Design of Algorithms             3
CS 3620 - Software Design and Architecture 3
CS 3710 - Database Systems 3
CS 4810 - Software Engineering 3

One of: 

CS 4820 - Software Systems Development Project or 
CS 4840 - Prototype Systems Development            

 

3
6

Two electives in Mathematical and Computational Sciences (at the 2000 level or higher)                          

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives: if CS 4820 taken 45
or if CS 4840 taken 42
Total Semester Hours of Credit    

120

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REQUIREMENTS FOR A MAJOR IN ACTUARIAL SCIENCE

Actuarial Science is the study of risk, usually risk associated with insurance, pension, and investment plans. Actuarial Science uses techniques from mathematics, statistics, business, economics, and finance. The Bachelor of Science with a Major in Actuarial Science prepares students to write the early exams required to become an Actuary. Actuaries are in demand as professionals who develop solutions for complex financial issues. Actuaries have excellent career opportunities following graduation as well as excellent co-op work opportunities during their studies. Read more about what actuaries' do, job prospects, and salaries on our departmental website.

The Major in Actuarial Science requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I 3
STAT 3220 - Probability and Mathematical Statistics II 3
STAT 3240 - Applied Regression Analysis 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning               3
MATH 3010 - Differential Equations 3

At least one of: 

MCS 2020 - Matlab Technology Lab
MCS 2040 - Visual Basic in Excel Technology Lab
OR MCS 2050 - GGY AXIS Technology Lab                    

1
AMS 2160 - Mathematics of Finance 3
AMS 2400 - Financial Mathematics & Investments 3
AMS 2410 - Financial Economics I       3
AMS 3410 - Financial Economics II 3
AMS 2510 - Actuarial Science I 3
AMS 3510 - Actuarial Science II 3
AMS 3310 - Advanced Corporate Finance for Actuaries 3
AMS 3730 - Advanced Insurance and Actuarial Practices 3
AMS 4540 - Loss Models I      3
AMS 4550 - Loss Models II 3
AMS 4580 - Credibility Theory 3
STAT 4110 - Statistical Simulation 3
STAT 4330 - Time Series I       3
STAT 4410 - Stochastic Processes       3
MCS 3920 - Numerical Analysis 3
ECON 1010 - Introductory Microeconomics  3
ECON 1020 - Introductory Macroeconomics 3
ACCT 1010 - Introduction to Accounting 3
BUS 2310 - Corporate Finance 3
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives 10
Total Semester Hours of Credit        120

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REQUIREMENTS FOR A MAJOR IN FINANCIAL MATHEMATICS

Financial Mathematics is the application of mathematical models to finance, usually to analyze markets and pricing. Financial Mathematics uses techniques from mathematics, statistics, business, finance, and economics. The Bachelor of Science in Financial Mathematics provides a solid foundation in Financial Mathematics, leading either to a career in the financial sector or to further training in advanced Financial Mathematics. Financial Mathematicians are in demand as professionals who develop solutions for complex financial issues and they have excellent career opportunities following graduation as well as excellent co-op work opportunities during their studies.

The Major in Financial Mathematics requires a total of 120 semester hours of credit, as described below:

  Credit Hours
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning               3
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I              3
STAT 3220 - Probability and Mathematical Statistics II             3
STAT 3240 - Applied Regression Analysis 3

At least one of: 

MCS 2020 - Matlab Technology Lab
MCS 2030 - R Technology Lab
OR MCS 2040 - Visual Basic in Excel Technology Lab

1
AMS 2160 - Mathematics of Finance 3
AMS 2400 - Financial Mathematics & Investments 3
AMS 2410 - Financial Economics I 3
AMS 3410 - Financial Economics II 3
AMS 4080 - Financial Mathematics II 3
AMS 4090 - Financial Mathematics III               3
AMS 4780 - Quantitative Risk Management 3
AMS 3910 - Mathematical Modelling 3
AMS 3310 - Advanced Corporate Finance for Actuaries 3
MATH 3010 - Differential Equations 3
MATH 3510 - Real Analysis  3
MATH 4710 - Partial Differential Equations 3
STAT 4330 - Time Series I       3

At least one of:

STAT 4410 - Stochastic Processes
OR MATH - 3920 Numerical Analysis

3
ECON 1010 - Introductory Microeconomics  3
ECON 1020 - Introductory Macroeconomics 3

At least one of:

ECON 2510 - Money and Financial Institutions
OR ECON 4050 - Financial Economics

3
ACCT 1010 - Introduction to Accounting           3
BUS 2310 - Corporate Finance 3

At least one of: 

BUS 3330 - Integrated Cases in Corporate Finance
BUS 3660 - Entrepreneurial Finance
BUS 4210 - Personal Finance
BUS 4390 - International Finance
OR BUS 4820 - International Strategy and Finance     

3
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives         10
Total Semester Hours of Credit 120

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REQUIREMENTS FOR A MAJOR IN ANALYTICS

(Specialization in Data Analytics)

Analytics is situated at the confluence of statistics, computer science and mathematics all centered on finding, interpreting and presenting meaningful patterns in data. We offer a Bachelor of Science in Analytics with specialization in either Data Analytics or Business Analytics, with co-operative education options available in both specializations. As data increasingly pervades our lives, graduates in Analytics are in high demand across a broad spectrum of fields including government, business and technology.

The Major in Analytics with a specialization in Data Analytics requires a total of 120 semester hours of credit, as described below: 

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3

At least one of: 

MCS 2010 - MAPLE Technology Lab
MCS 2020 - Matlab Technology Lab
OR MCS 2030 - R Technology Lab       

1
MATH 2420 -  Combinatorics I 3
MATH 3430 - Combinatorics II 3
AMS 2940 - Optimization       3
AMS 3770 - Combinatorial Optimization 3
AMS 3910 - Mathematical Modelling 3
MATH 3010 - Differential Equations 3
MATH 3610 - Group Theory     3
STAT 3210 - Probability and Mathematical Statistics I 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4550 - Data Analysis and Inference 3
STAT 4660 - Data Visualization and Mining 3
CS 2610 - Data Structures and Algorithms 3
CS-2910 - Computer Science III 3
CS 3710 - Database Systems 3
CS 3610 - Analysis and Design of Algorithms             3
CS 4120 - Machine Learning 3
CS 4440 - Data Science 3

Two  electives in Mathematical or Computational Sciences (at the 2000 level or higher)

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences    1
MCS 4210 - Professional Communication and Practice             3
Additional general electives 19
Total Semester Hours of Credit      120

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REQUIREMENTS FOR A MAJOR IN ANALYTICS

(Specialization in Business Analytics)

The Major in Analytics with a specialization in Business Analytics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II                 3
MATH 2620 - Linear Algebra II                3
MATH 2720 - Mathematical Reasoning  3

At least one of:

MCS 2010 - MAPLE Technology Lab
MCS 2020 - Matlab Technology Lab 
OR MCS 2030 - R Technology Lab         

1
MATH 2420 - Combinatorics I 3
MATH 3430 - Combinatorics II 3
AMS 2940 - Optimization       3
AMS 3770 - Combinatorial Optimization 3
AMS 3910 - Mathematical Modelling 3
MATH 3010 - Differential Equations 3
STAT 3210 - Probability and Mathematical Statistics I                 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4660 - Data Visualization and Mining 3

Two electives in the Mathematical and Computational Sciences (at the 3000 level or higher)

6
CS 2610 - Data Structures and Algorithms 3
CS 2910 - Computer Science III 3
CS 3710 - Database Systems 3
ACCT 1010 - Introduction to Financial Accounting 3
BUS 1410 - Marketing 3
BUS 1710 - Organizational Behaviour 3

At least five of: 

ACCT 2210 - Managerial Accounting
BUS 2650 - Introduction to Entrepreneurship
BUS 2880 - Research and Evidence-Based Management
BUS 2720 - Human Resource Management
BUS 3010 - Business Law
BUS 3330 - Integrated Cases in Corporate Finance
BUS 3510 - Operations Management
BUS 3710 - Entrepreneurship and New Ventures
BUS 4650 - Project Management
OR BUS 4880 - Developing Management Skills

15
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives 10
Total Semester Hours of Credit       120

Note: Students who complete the Major in Analytics with a specialization in Business Analytics and obtain grades of at least 60% in seven of the Business courses can also obtain a Certificate in Business.

 

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REQUIREMENTS FOR A MAJOR IN MATHEMATICS WITH ENGINEERING

The specialization augments the Mathematics major with Engineering courses offered through UPEI’s School of Sustainable Design Engineering. The Bachelor of Science in Mathematics with Engineering provides a foundational Engineering program combined with more advanced mathematical training than is received in an Engineering Degree program.

The Major in Mathematics with Engineering requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
STAT 2220 - Introductory Statistics II 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3
MATH 3010 - Differential Equations 3
MATH 3310 - Complex Variables 3

At least one of:

MATH 3510 - Real Analysis
OR Math 3610 Group Therapy

3

Two electives in Mathematical and Computational Sciences (at the 3000 level or higher)

6
PHYS 1110 and 1120 - General Physics I and II 6
CHEM 1110 and 1120 - General Chemistry I and II 6
ENGN 1210 - Design 1: Engineering Communications 3
ENGN 1220 - Design 2: Engineering Analysis 3
ENGN 1510 - Engineering and the Biosphere 3
ENGN 2210 - Design 3: Engineering Projects I 3
ENGN 2220 - Design 4: Engineering Projects II 3
ENGN 2310 - Strength of Materials 3
ENGN 2340 - Engineering Dynamics 3
ENGN 2610 - Thermofluids I 3
ENGN 2810 - Electrical Circuits I 3
Two electives in Engineering        6
Additional general electives 24
Total Semester Hours of Credit       120

Note: Mathematics with Engineering Majors may substitute ENGN 1320 for CS 1510, and CS 1610 or MCS 3920 for CS 1520.

 

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REQUIREMENTS FOR A MAJOR IN COMPUTER SCIENCE (Specialization in Video Game Programming)

The Major in Computer Science with a specialization in Video Game Programming requires a total of 120 semester hours of credit, as described below.  

  Credits
The Common Core 23
CS 1610 - Digital Systems 3

At least one of:

CS 2120 - Mobile Device Development – iOS 
OR CS 2130 - Mobile Device Development – Android

3
CS 2520 - Computer Organization and Architecture 3
CS 2610 - Data Structures and Algorithms 3
CS 2620 - Comparative Programming Languages 3
CS 2820 - Programming Practices 3
MATH 2420 - Combinatorics I 3
CS 3110 - Video Game Design 3
MCS 3320 - Theory of Computing 3
CS 3420 - Computer Communications         3
CS 3520 - Operating Systems 3
CS 3610 - Analysis and Design of Algorithms 3
CS 3620 - Software Design and Architecture 3
CS 3710 - Database Systems 3
CS 4350 - Computer Graphics Programming 3
CS 4360 -  Advanced Computer Graphics Programming 3

At least two of: 

CS 4060 - Cloud Computing
CS 4120 - Machine Learning
CS 4440 - Data Science
OR CS 4610 - Wireless Sensor Networks

6
CS 4650 - Video Game Architecture 3
CS 4810 - Software Engineering 3
CS 4830 - Video Game Programming Project            6

Two electives in the Mathematical and Computational Sciences (at the 2000 level or higher)

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives 21
Total Semester Hours of Credit 120

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Acceptance to an Honours program

Students in the Mathematics, Statistics and Computer Science programs have an Honours option. Permission of the School of Mathematical and Computational Sciences is required for admission to an Honours program. Students must normally have a minimum average of 70% in all previous courses. Normally, the School expects an average of 75% in all previous Mathematical and Computational Sciences courses. Admission is contingent upon the student finding a project advisor and acceptance by the School of the topic for the Honours project. Students interested in doing Honours are strongly encouraged to consult with the Associate Dean of the School of Mathematical and Computational Sciences as soon as possible, and no later than January 31 of the student’s third year. To receive the Honours designation, in addition to successful completion of the Honours project, normally students must maintain an average of at least 75% in all courses in the School of Mathematical and Computational Sciences.

REQUIREMENTS FOR HONOURS IN MATHEMATICS

The Honours in Mathematics program requires a total of 126 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910  Multivariable and Vector Calculus              4
STAT 2220     Introductory Statistics II                 3
MATH 2620   Linear Algebra II 3
MATH 2720   Mathematical Reasoning  3

At least one of: MCS 2010 - MAPLE Technology Lab OR MCS 2020 - Matlab Technology Lab

1
MATH 2420  Combinatorics I 3
MATH 3510   Real Analysis  3
MATH 3610  Group Theory 3
MATH 3010  Differential Equations 3
STAT   3210  Probability and Mathematical Statistics I 3
MATH 3310  Complex Variables 3
MCS 4900     Honours Project 6

Four electives in the Mathematical and Computational Sciences (at the 2000 level or higher, with at least two at the 4000 level or higher)

12
MCS 3050  Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit    126

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REQUIREMENTS FOR HONOURS IN STATISTICS

The Honours in Statistics program requires a total of 126 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910  Multivariable and Vector Calculus 4
STAT 2220    Introductory Statistics II 3
MATH 2620  Linear Algebra II 3
MATH 2720  Mathematical Reasoning  3
MCS 2030    R Technology Lab 3
STAT 3210  Probability and Mathematical Statistics I                 3
STAT 3220  Probability and Mathematical Statistics II 3
STAT 3240   Applied Regression Analysis 3
STAT 4550  Data Analysis and Inference 3
STAT 4240  Experimental Design       3
STAT 4330  Time Series I       3
STAT 4110   Statistical Simulation 3
STAT 4410   Stochastic Processes 3
MCS 4900   Honours Project 6

Two electives in the Mathematical and Computational Science (at the 3000 level or higher)

6
MCS 3050  Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit 126

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REQUIREMENTS FOR HONOURS IN COMPUTER SCIENCE

The Honours in Computer Science requires a total of 126 semester hours of credit, as described below.  
 

  Credits
The Common Core 23
CS 1610 Digital Systems 3
CS 2520  Computer Organization and Architecture 3
CS 2610   Data Structures and Algorithms 3
CS 2620   Comparative Programming Languages 3
CS 2820   Programming Practices 3
MATH 2420  Combinatorics I 3
MATH 2910  Multivariable Calculus 4
MCS 3320   Theory of Computing 3
CS 3420   Computer Communications 3
CS 3520   Operating Systems 3
CS 3610   Analysis and Design of Algorithms             3
CS 3620   Software Design and Architecture 3
CS 3710   Database Systems 3

At least one of: CS 4110 - Artificial Intelligence and Automated Reasoning OR CS 4120 - Machine Learning

3
CS 4810   Software Engineering 3
MCS 4900  Honours Research Project 6

Four electives in the Mathematical and Computational Sciences (at the 2000 level or higher)

12
MCS 3050 Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives 35
Total Semester Hours of Credit     126

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REQUIREMENTS FOR A MINOR IN MATHEMATICS

Students may obtain a Minor in Mathematics by completing at least 24 semester hours of credit in Mathematics defined as follows:

Math 1910-1920 - Single Variable Calculus I & II 8
Math 2610 - Linear Algebra I 3
Math 2910 - Multivariable and Vector Calculus 4
plus 3 semester hours of credit in Mathematics at the 3000 level or higher, and an additional 6 semester hours of credit of Mathematics at the 2000 level or above 9
Total Semester Hours of Credit 24

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REQUIREMENTS FOR A MINOR IN STATISTICS

Students may obtain a Minor in Statistics by completing at least 23 semester hours of credit in Mathematics and Statistics defined as follows:

MATH 1910-1920 - Single Variable Calculus I  & II 8
STAT 2210-2220 - Introductory Statistics I & II 6
MATH 2610 - Linear Algebra I 3
STAT 3210 -  Probability and Mathematical Statistics I 3
plus 3 semester hours of credit in Statistics at the 3000 level or higher 3
Total Semester Hours of Credit 23

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REQUIREMENTS FOR A MINOR IN COMPUTER SCIENCE

Students may obtain a Minor in Computer Science by completing at least 21 semester hours of credit in Computer Science defined as follows:

CS 1910-1920 - Computer Science I & II  6
CS 2520 - Computer Organization and Architecture  3
CS 2610 - Data Structures and Algorithms  3

plus 3 semester hours of credit in Computer Science at the 3000 level or higher, and an additional 6 semester hours of credit in Computer Science at the 2000 level or higher

9
Total Semester Hours of Credit  21
 

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MATHEMATICAL AND COMPUTATIONAL SCIENCES CO-OP PROGRAM

The Mathematical and Computational Sciences Co-op program is an integrated approach to university education that enables students to alternate academic terms on campus with work terms in relevant and supervised employment. The Co-op program consists of eight academic terms, at least three work terms and a series of professional development workshops and seminars. It is available as an option to full-time students enrolled in Major and Honours programs. Application to the co-op program is made in the student’s second year of study. Students must complete 126 semester hours of credit to graduate with the Co-op designation, and no credit will be given for any Co-op work term course, unless at least three work terms are successfully completed.

See the Co-op Education (Mathematical and Computational Sciences) page for complete program details.

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ADMISSION TO SCIENCE CALCULUS

The First-year Calculus courses for most science students are Math 191 and Math 1920. In addition to Grade XII academic Mathematics (or equivalent), a passing grade on an Assessment Test written during the first week of classes is required as a prerequisite for Math 1910. The Assessment Test covers the standard pre-calculus topics of the High School curriculum (arithmetic, algebra, trigonometry, analytic geometry and the basic theory of functions). This test is of 90 minutes duration and is given during the first week of classes.

Students who do not pass the assessment test may have the option of enrolling in a special section of Math 1910 incorporating additional tutorials reviewing pre-Calculus materials. See the Associate Dean of the School of Mathematical and Computational Sciences for details.


 

Courses

Course code prefixes

In the School of Mathematical and Computational Sciences, there are five course prefixes:

Mathematics (MATH) Courses

MATH-1010 - ELEMENTS OF MATHEMATICS This course provides an introduction to several mathematical topics at the university level, and is intended for students majoring in a discipline other than Mathematical and Computational Sciences, or the Natural Sciences. The course consists of four modules: (1) Sets and Logic, (2) Number Theory, (3) Geometry, (4) Mathematical Systems. NOTE: Credit will not be given jointly for this course and any other 1000-level Mathematics course. Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1110 - FINITE MATHEMATICS This course introduces students to finite mathematical techniques and to mathematical models in business, life and the social sciences. The course begins with an introduction to mathematical models, types of models, and conversion of verbal models to mathematical models. Topics covered include systems of linear equations and matrices, linear inequalities and linear programming, sets, counting and probability. NOTE: Credit for Mathematics 1110 will not be allowed if taken concurrent with or subsequent to Mathematics 2610. Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1120 - CALCULUS FOR THE MANAGERIAL, SOCIAL AND LIFE SCIENCES This course provides an introduction to calculus for students in the managerial, social and life sciences. The main emphasis of the course is the development of techniques of differentiation and integration of algebraic, exponential and logarithmic functions. Applications of derivatives and integrals are also discussed. NOTE: Credit will not be given jointly for this course and Math 1910 Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1910 - SINGLE VARIABLE CALCULUS I This course is an introduction to differential and integral calculus of functions of a single variable. The course is intended primarily for majors in the Mathematical and Computational Sciences, Engineering and the Physical Sciences, as well as those planning to continue with further Mathematics courses. The concepts of limits, continuity and derivatives are introduced and explored numerically, graphically and analytically. The tools of differential calculus are applied to problems in: related rates; velocity and acceleration; extrema of functions; optimization; curve sketching; and indeterminate forms. The concepts of definite and indefinite integrals are introduced, and the relation between the two integrals is discovered via the Fundamental Theorem of Calculus. Four lecture hours per week Semester hours of credit: 4 Prerequisite: Prerequisite: Grade XII academic Mathematics [and a passing grade on the Assessment Test]
PREREQUISITE: Math-1910T (concurrent with taking this course)
4 hours credit
MATH-1910R - PRE-CALCULUS REVIEW TUTORIAL
MATH-1910T - MATH 1910 TUTORIAL
PREREQUISITE: Math 1910 (concurrent with taking this course)
MATH-1920 - SINGLE VARIABLE CALCULUS II This course is a continuation of integral calculus of functions of a single variable and an introduction to sequences and series. Techniques of integration are studied, including improper integrals and numerical integration, and the tools of integral calculus are used to compute areas, volumes and arc lengths; and are applied to problems in physics and differential equations. Sequences, series, tests for convergence, Taylor series and Taylor polynomials are studied. Four lecture hours per week Semester hours of credit: 4
PREREQUISITE: Math-1920T (concurrent with taking this course)
4 hours credit
MATH-1920T - Math 1920 Tutorial
PREREQUISITE: Mathematics 1920 (concurrent with taking this course)
MATH-2420 - COMBINATORICS I This course offers a survey of topics in discrete mathematics that are essential for students majoring in the Mathematical and Computational Sciences. Topics include: logic, proof techniques such as mathematical induction, recursion, counting methods, and introductory graph theory. Three lecture hours per week
PREREQUISITE: Math 1920 (prior to taking this course)
3 hours credit
MATH-2610 - LINEAR ALGEBRA I This course introduces some of the basic concepts and techniques of linear algebra to students of any major. The emphasis is on the interpretation and development of computational tools. Theory is explained mainly on the basis of two or three-dimensional models. Topics covered are: matrices; determinants; systems of equations; vectors in two and three-dimensional space including dot and cross products, lines, and planes; concepts of linear independence, basis, and dimension explained with examples; linear transformations and their matrices; eigenvectors and eigenvalues. Three lecture hours per week Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-2620 - LINEAR ALGEBRA II This course continues MATH 2610 with further concepts and theory of linear algebra. Topics include vector spaces, orthogonality, Gram-Schmidt Process, canonical forms, spectral decompositions, inner product spaces and the projection theorem. Three lecture hours a week
PREREQUISITE: Math 1910 and Math 2610 (prior to taking this course)
3 hours credit
MATH-2720 - MATHEMATICAL REASONING This course provides students with experience in writing mathematical arguments. It covers first-order logic, set theory, relations, and functions. The ideas and proof techniques are considered in the context of various mathematical structures such as partial orders, graphs, number systems, and finite groups. Three lecture hours per week
3 hours credit
MATH-2810 - FOUNDATIONS OF GEOMETRY This course presents an axiomatic base for Euclidean geometry and an insight into the interdependence of the various theorems and axioms of that geometry and non-Euclidean geometries. Topics include: incidence and separation properties for points, lines, planes and space; congruence properties; geometric inequalities; similarity properties; and geometric constructions. Three lecture hours per week
PREREQUISITE: Six credit hours of First Year Mathematics (prior to taking this course)
3 hours credit
MATH-2820 - MATHEMATICAL PHYSICS (FORMERLY 3810) (Please note this course will not be offered until January, 2017) This course is an introduction to some of the mathematical methods commonly used in the physical sciences and engineering, with an emphasis on applications in physics. Topics include: vector analysis in curvilinear coordinates, tensor analysis (with applications in fluid mechanics), introduction to complex variables, Fourier series, calculus of variations and applications. Cross-listed with Physics (cf. Physics 2820) Three hours lecture per week
PREREQUISITE: Math 2910 and either Physics 1120 or Physics 1220 (prior to taking this course)
3 hours credit
MATH-2910 - MULTIVARIABLE AND VECTOR CALCULUS This course continues from Math 1920 and is an introduction to multivariable differentiation and integration and vector calculus. Topics include parametric representation of curves; polar coordinates; vectors; dot and cross products; curves and surfaces in space; calculus of vector-valued functions; functions of several variables; partial differentiation; directional derivatives; tangent planes; local and constrained maxima and minima; double and triple integrals; changes of variables in multiple integrals; vector fields; line and surface integrals; gradient, divergence and curl; Green's, Stokes' and Divergence Theorems. Four lecture hours per week Semester hours of credit: 4
PREREQUISITE: Math 1920 (prior to taking this course)
4 hours credit
MATH-2910T - ADDITIONAL LECTURE
MATH-3010 - DIFFERENTIAL EQUATIONS This course introduces the basic theory of differential equations, considers various techniques for their solution, and provides elementary applications. Topics include linear equations; separable equations; linear independence and Wronskian; second-order equations with constant coefficients; nonhomogeneous equations; applications of first- and second-order equations; Laplace and inverse Laplace transforms, and their application to initial-value problems; series solutions about ordinary and singular points; and Fourier series. Three lecture hours per week
PREREQUISITE: Math 1920 (prior to taking this course)
3 hours credit
MATH-3210 - PROBABILITY AND MATH STATS I
3 hours credit
MATH-3220 - PROBABILITY AND MATH STATS II
3 hours credit
MATH-3240 - APPLIED REGRESSION ANALYSIS
3 hours credit
MATH-3310 - COMPLEX VARIABLES This is a first course in complex variables. The aim is to acquaint students with the elementary complex functions, their properties and derivatives, and with methods of integration. Topics covered include: definition and development of complex numbers as ordered pairs; geometric representation; basic formulas and inequalities involving argument and conjugates; roots of complex numbers, limit, continuity, and derivative; Cauchy Riemann conditions; harmonic functions; properties of trigonometric, hyperbolic, logarithmic, exponential, and inverse trigonometric functions; bilinear transformation; integration; Cauchy Integral Theorem and Formula; residues and poles; Laurent and Taylor's series; and improper integrals. Three lecture hours per week
PREREQUISITE: Math 2910 (prior to taking this course)
3 hours credit
MATH-3420 - NUMBER THEORY This first course in number theory will include the following topics: equivalence of the principles of induction and the well-ordering principle; division algorithm; positional notation and repeating decimals; greatest common divisor; Euclidean Algorithm; Fundamental Theorem of Arithmetic; Pythagorean Triplets; Prime Numbers Theorem; Mersenne and Fermat Numbers; congruences; Euler's Phi-function; Chinese Remainder Theorem; Diophantine Equations; Theorems of Lagrange and Wilson; Quadratic Reciprocity Law of Gauss; Legendre symbol and primitive roots; perfect numbers; multiplicative number- theoretic functions; Moebius inversion. Three lecture hours per week
PREREQUISITE: Six credit hours of Mathematics at the 2000 level or higher (prior to taking this course)
3 hours credit
MATH-3430 - COMBINATORICS II This course continues MATH 2420, with the examination of advanced counting techniques, binomial coefficients, and generating functions. Other topics include relations, partial orders, and Steiner Triple systems. Three lecture hours per week
PREREQUISITE: Math 2420 (prior to taking this course)
3 hours credit
MATH-3510 - REAL ANALYSIS This is a first course in real analysis. Topics include: the reals as a complete ordered field; closed and open sets; Bolzano-Weierstrass and Heine-Borel Theorems; Cauchy Sequences; limits and continuity; derivative; Mean Value Theorem; Riemann Integral; and the Fundamental Theorem of Calculus. Three lecture hours per week
PREREQUISITE: Math 1920 and Math 2720 (prior to taking this course)
3 hours credit
MATH-3520 - REAL ANALYSIS II
3 hours credit
MATH-3610 - GROUP THEORY An introduction to group theory, including: cyclic groups, symmetric groups, subgroups and normal subgroups, Lagrange's theorem, quotient groups and homomorphisms, isomorphism theorems, group actions, Sylow's theorem, simple groups, direct and semidirect products, fundamental theorem on finitely generated Abelian groups. Three lecture hours per week
PREREQUISITE: Math 2720 (prior to taking this course)
3 hours credit
MATH-3710 - GRAPH THEORY This course is an introduction to the ideas, methods, and applications of graph theory. Topics include graph connectivity, graph factors and factorizations, planar graphs, and colourings. Three lecture hours per week
PREREQUISITE: Math 2420 or Math 2720 (prior to taking this course)
3 hours credit
MATH-4020 - POINT-SET TOPOLOGY A first course in topology, covering some review of set theory; cardinal numbers; binary relations; metric spaces, convergence and continuity in metric spaces; topological spaces, bases, sub- spaces; continuity in general; homeomorphism; product spaces; separation axioms; compactness; connectedness. Three lecture hours per week
PREREQUISITE: Math 3510 (prior to taking this course)
3 hours credit
MATH-4520 - MEASURE THEORY AND INTEGRATION A first course in measure theory, covering measure as a generalization of length, outer measure, sigma-algebras, measurability, construction of measures, Lebesgue measure on the real line, measurable functions and the Lebesgue integral. Additional topics may include and convergence theorems, product measures and Fubini Theorem. Three lecture hours per week
PREREQUISITE: Math 3510 (prior to taking this course)
3 hours credit
MATH-4530 - FUNCTIONAL ANALYSIS This first course in functional analysis covers topics like: metric spaces, Banach spaces, function spaces, Hilbert spaces, generalized Fourier series and linear operators. Three lecture hours per week
PREREQUISITE: Math 2620 and Math 3510 (prior to taking this course)
3 hours credit
MATH-4620 - RING AND FIELD THEORY Introduction to ring and field theory, including: polynomial rings, matrix rings, ideals and homomorphisms, quotient rings, Chinese remainder theorem, Euclidean domains, principal ideal domains, unique factorization domains, introduction to module theory, basic theory of field extensions, splitting fields and algebraic closures, finite fields, introduction to Galois theory. Three lecture hours per week
PREREQUISITE: Math 3610 (prior to taking this course)
3 hours credit
MATH-4710 - PARTIAL DIFFERENTIAL EQUATIONS This course is an introduction to the theory and application of partial differential equations. Topics include: first-order equations and characteristic curves; classification of second-order equations as parabolic, hyperbolic or elliptic; Laplace, wave and diffusion equations, and their physical origins; solution using Fourier series; and separation of variables. Three lecture hours per week
PREREQUISITE: Math 2910 and Math 3010 (prior to taking this course)
3 hours credit
MATH-4720 - DYNAMICAL SYSTEMS This course is a study of the long-term qualitative behaviour of solutions of systems of differential or difference equations. Topics include: non-linear systems, linearization, numerical and graphical methods, equilibria, phase space, stability, bifurcations, strange attractors, and chaos. Applications to physics, biology and other sciences are studied. Three lecture hours per week
PREREQUISITE: Math 2610, Math 2910, and Math 3010 (prior to taking this course)
3 hours credit
MATH-ELEC1 - MATH ELECTIVE 1000 LEVEL
3 hours credit
MATH-ELEC2 - MATH ELECTIVE 2000 LEVEL
3 hours credit
MATH-ELEC3 - MATH ELECTIVE 3000 LEVEL
3 hours credit
MATH-ELEC4 - MATH ELECTIVE 4000 LEVEL
3 hours credit

Statistics (STAT) Courses

STAT-2210 - INTRODUCTORY STATISTICS I The main objective of this course is to introduce the basic concepts of descriptive statistics, statistical inference, and the use of statistical software such as MINITAB to students in any discipline. More time is spent on statistical inference than on descriptive statistics. Topics include frequency distributions, descriptive statistics, rules of probability, discrete and continuous probability distributions, random sampling and sampling distributions, confidence intervals, one- and two-tail tests of hypotheses, and correlation and linear regression. NOTE: Credit will not be allowed for Statistics 2210 if a student has received credit for any of the following courses: Business 2510, Education 4810, Psychology 2710 and Sociology 3320. Prerequisite: Grade XII academic Mathematics.
3 hours credit
STAT-2220 - INTRODUCTORY STATISTICS II The course builds upon the knowledge developed in Introductory Statistics I and introduces students to statistical techniques commonly used in research. Topics include linear regression and multiple linear regression, residual analysis, simple ANOVA models, categorical data analysis, simple sampling models, and common distributions (including binomial, Poisson, and exponential). Three lecture hours per week
PREREQUISITE: Statistics 2210 (prior to taking this course)
3 hours credit
STAT-3210 - PROBABILITY AND MATHEMATICAL STATISTICS I This course is an introduction to the theoretical basis of statistics for students who have completed Introductory Statistics. The study concentrates on the mathematical tools required to develop statistical methodology. Topics covered include: probability, continuous and discrete random variables, moment generating functions, multivariate probability distributions and functions of random variables. Three lecture hours per week
PREREQUISITE: Math 2910 and Stat 2220 or permission of the instructor (prior to taking this course)
3 hours credit
STAT-3220 - PROBABILITY AND MATHEMATICAL STATISTICS II This course builds on the mathematical foundation developed in Statistics 3210 and introduces the student to the theory of statistical inference. Topics covered include: sampling distributions and central limit theory, methods of estimation, hypothesis testing, least squares estimation of linear models, and an introduction to Bayesian inference. Three lecture hours per week
PREREQUISITE: Statistics 3210 (prior to taking this course)
3 hours credit
STAT-3240 - APPLIED REGRESSION ANALYSIS This course builds upon the basis of inference studied in Statistics 2210 and provides students with an advanced knowledge of regression techniques. Topics covered are simple and multiple linear regression techniques, matrix notation, the design matrix, model building techniques, residual analysis, and non-linear regression. Three lecture hours per week
PREREQUISITE: Statistics 2210 and Math 2610 (prior to taking this course)
3 hours credit
STAT-4110 - STATISTICAL SIMULATION This course introduces statistical simulation, and its use as a tool to investigate stochastic phenomena and statistical methods. Topics include the building and validation of stochastic simulation models useful in computing, operations research, engineering and science; related design and estimation problems; variance reduction; and the implementation and the analysis of the results. Three lecture hours per week
PREREQUISITE: Statistics 3220 (prior to taking this course)
3 hours credit
STAT-4240 - EXPERIMENTAL DESIGN This course builds upon the basis of inference studied in Statistics 2210 and Statistics 3240 to include statistical techniques commonly used in experimental studies. Students will study topics such as analysis of variance models, hypothesis testing in ANOVA models, randomization, and blocking techniques. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4280 - GENERALIZED LINEAR MODELS This course covers the basic theory, methodology and applications of generalized linear models. Topics include logistic regression, probit regression, binomial regression, Poisson regression, overdispersion, quasi-likelihood, and the exponential family. Three lecture hours per week
PREREQUISITE: Statistics 3220 and Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4330 - TIME SERIES I This course is an introduction to Time Series methods, including: stationary models, trends and seasonality, stochastic Time Series models, autoregressive and moving average processes and an introduction to Time Series forecasting. ARIMA models. Seasonal Time Series and Spectral Analysis are also covered. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4340 - TIME SERIES II This course includes topics from Time Series Econometrics, including Maximum Likelihood and Least Squares Estimation of ARIMA Models and GARCH Models, Wavelets and Financial Models. Non-stationary Time Series, multivariate Time Series and panel cointegration analysis are also covered. Three lecture hours per week
PREREQUISITE: Statistics 4330 (prior to taking this course)
3 hours credit
STAT-4410 - STOCHASTIC PROCESSES This course is an introduction to the branch of probability theory that deals with the analysis of systems that evolve over time. Topics include random walks, Markov chains, Poisson processes, continuous time Markov chains, birth and death processes, exponential models, and applications of Markov chains. Three lecture hours per week
PREREQUISITE: Statistics 3220 (prior to taking this course)
3 hours credit
STAT-4550 - DATA ANALYSIS AND INFERENCE This course is an introduction to data analysis with a focus on regression. Topics include: initial examination of data, correlation, and simple and multiple regression models using least squares. Inference for regression parameters, confidence and prediction intervals, diagnostics and remedial measures interactions and dummy variables, variable selection, least squares estimation and inference for non-linear regression will also be discussed. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4660 - DATA VISUALIZATION AND MINING This course introduces students to the statistical methods involved in visualization of high dimensional data, including interactive methods directed at exploration and assessment of structure and dependencies in data. Topics include methods for finding groups in data including cluster analysis, dimension reduction methods including multi-dimensional scaling, pattern recognition, and smoothing techniques. Three lecture hours per week
PREREQUISITE: Math 2620, Math 2910, and Statistics 3210 (prior to taking this course)
3 hours credit
STAT-4740 - MULTIVARIATE ANALYSIS This course deals with the statistics of observation and analysis of more than one output variable. Topics include estimation and hypothesis testing for multivariate normal data, principal component analysis and factor analysis, discriminant analysis, cluster analysis, and correspondence analysis. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-ELEC1 - STATISTICS ELECTIVE 1000 LEVEL
3 hours credit
STAT-ELEC2 - STATISTICS ELECTIVE 2000 LEVEL
3 hours credit
STAT-ELEC3 - STATISTICS ELECTIVE 3000 LEVEL
3 hours credit
STAT-ELEC4 - STATISTICS ELECTIVE 4000 LEVEL
3 hours credit

Computer Science (CS) Courses

CS-1210 - INTRODUCTION TO COMPUTER PROGR
3 hours credit
CS-1410 - INTRODUCTION TO COMPUTER PROGRAMMING FOR SCIENTISTS This course is an introduction to computer programming for non-computer science majors. Topics include problem-solving, algorithm design, data types, control structures, repetition, loops, nested structures, modular programming and arrays. Three lecture hours and 1.5 hours of laboratory session per week. NOTE: Credit will be allowed for only one of CS 1410 or Engineering 1320. As well, CS 1410 may not be taken concurrently with, or after, CS 1510. Prerequisite: Grade XII academic mathematics
PREREQUISITE: Computer Science 1410L (concurrent with taking this course)
3 hours credit
CS-1410L - Computer Science 1410 Lab
PREREQUISITE: Computer Science 1410 (concurrent with taking this course)
CS-1520L - Computer Science 1520 Programming Workshop
PREREQUISITE: Computer Science 1520 (concurrent with taking this course)
CS-1610 - DIGITAL SYSTEMS This course provides an introduction to digital systems, beginning with elementary components such as logic gates, from which are constructed components such as adders and comparators, and progressing to more complex systems such as programmable logic devices, memory and processor units. Students acquire skills in the design and analysis of combinational and sequential digital systems, CAD design and simulation tools for complex systems, and construction of digital systems based upon a modular methodology. Three lecture hours and a three-hour laboratory session per week
PREREQUISITE: Computer Science 1610L (concurrent with taking this course)
3 hours credit
CS-1610L - Computer Science 1610 Lab
PREREQUISITE: Computer Science 1610 (concurrent with taking this course)
CS-1910 - COMPUTER SCIENCE I This course is an introduction to computer programming and is designed for both Computer Science majors and non-majors. Emphasis is on problem solving and software development using a modern high level object-oriented language. Topics include: the programming process; language syntax and semantics; data types; expressions; input and output; conditionals; loops; arrays; functions/methods and text files. The course follos an "objects late" strategy, deferring in-depth discussions of object-orientated concepts to Computer Science 192. Prerequisite: Grade XII academic mathematics.
PREREQUISITE: Computer Science 1910L (concurrent with taking this course)
3 hours credit
CS-1910L - Computer Science 1910 Lab
PREREQUISITE: Computer Science 1910 (concurrent with taking this course)
CS-1920 - COMPUTER SCEINCE II This course continues the development of object-oriented programming. Topics include class design; inheritance; interfaces and polymorphism; collection classes; searching and sorting; recursion; exception handling; the Model-View-Controller pattern; and graphical user interfaces.
PREREQUISITE: Computer Science 1920L; (concurrent with taking this course)
3 hours credit
CS-1920L - Computer Sceince 1920 Lab
PREREQUISITE: Computer Sceince 1920; (concurrent with taking this course)
CS-2060 - WEB DEVELOPMENT AND PROGRAMMING In this course, students learn to create websites that involve server-side scripting and database operations. While one specific scripting language is used to acquire web development and programming skills, students are exposed to a spectrum of scripting languages, enabling them to easily adapt to others. Three hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2120 - MOBILE DEVICE DEVELOPMENT - iOS This course introduces the student to programming for mobile devices that use iOS. The course will present a study of the architecture, operating system, and programming for these devices. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2130 - MOBILE DEVICE DEVELOPMENT - ANDROID This course introduces the student to programming for mobile devices that use the Android platform. The course will present a study of the architecture, operating system and programming language of these devices. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or CS-1920 (prior to taking this course)
3 hours credit
CS-2520 - COMPUTER ORGANIZATION AND ARCHITECTURE This course provides a basic understanding of the organization and architecture of modern computer systems. It examines the function and design of major hardware components both from a designer's perspective and through assembly language programming. Topics include components and their interconnection, internal/external memory, input/output subsystems, processors, computer arithmetic, instruction sets, addressing modes, and pipelining. Three hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2610 - DATA STRUCTURES AND ALGORITHMS This course continues the study of data structures, recursive algorithms, searching and sorting techniques, and general strategies for problem solving. It also introduces complexity analysis and complexity classes. Three lecture hours per week
PREREQUISITE: Computer Science 1520 and six credit hours of Mathematics (prior to taking this course)
3 hours credit
CS-2620 - COMPARATIVE PROGRAMMING LANGUAGES This course examines the principal features of major types of programming languages, including procedural, logical, functional and object-oriented languages. Features include parameter-passing mechanisms, control structures, scope, and binding rules. Each language type is illustrated by considering a specific language. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-2710 - PRACTICAL EMBEDDED SYSTEMS This course introduces students to the concept of embedded systems architectures, the interconnection of sensors and actuators to such systems, and the usage of such platforms for data acquisition and control of automated systems. Popular microcontroller units and system-on-chip platforms will be examined. Three lecture hours per week
PREREQUISITE: Computer Science 1210 or Computer Science 1410 or Computer Science 1510 or Engineering 1310 or CS-1920 (prior to taking this course)
3 hours credit
CS-2820 - PROGRAMMING PRACTICES This course introduces the student to development in the Unix/Linux environment. Topics include development tools, shell programming, common utility programs, processes, file/directory management, IDEs, testing/debugging, version control, and an introduction to software engineering. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 permission of the instructor (based on completion of CS 1510 with first class standing) (prior to taking this course)
3 hours credit
CS-2910 - COMPUTER SCIENCE III This is the third course in the Computer Science programming sequence. It covers more advanced programming concepts in an object oriented language. It also serves as an introduction to data structures and software engineering. Topics included: the programming toolchain; threads; class generics; lists, stacks, queues and binary trees; streams and binary I/O, object serialization, networking (sockets and web interface); introduction to software engineering; relational database connectivity; and XML parsing.
PREREQUISITE: Computer Science 1920 and 6 Math credits (prior to taking this course)
3 hours credit
CS-2910L - Computer Science 2910 Lab
PREREQUISITE: Computer Science 2910; (concurrent with taking this course)
CS-2920 - DATA STRUCTURES AND ALGORITHMS This course continues the study of data structures, recursive algorithms, searching and sorting techniques, and general strategies for problem solving. It also introduces complexity analysis and complexity classes. Three lecture hours per week
PREREQUISITE: Computer Science 2910 and 6 Math credits (prior to taking this course)
3 hours credit
CS-2920L - Computer Science 2920 Lab
PREREQUISITE: Computer Science 2920; (concurrent with taking this course)
CS-3110 - VIDEO GAME DESIGN This course focuses on the process from initial idea to final design of a video game. Students will craft a game document from an original concept of their own creation and create a prototype of the game based on that document. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3210 - HUMAN-COMPUTER INTERFACE DESIGN This course is an introduction to the design and evaluation of software interfaces and webpages. The course focuses on user-centered design and includes topics such as user analysis and modelling, iterative prototyping, usability testing, designing for the web, internationalization and localization. Three hours per week
PREREQUISITE: Computer Science 1520 (prior to taking this course)
3 hours credit
CS-3220 - INTRODUCTION TO BIOINFORMATICS This course is an introduction to bioinformatics, with a focus on a practical guide to the analysis of data on genes and proteins. It familiarizes students with the tools and principles of contemporary bioinformatics. Students acquire a working knowledge of a variety of publicly available data and computational tools important in bioinformatics, and a grasp of the underlying principles enabling them to evaluate and use novel techniques as they arise in the future. Cross-listed with Biology, Pathology/Microbiology, Human Biology (cf. Biology 3220, VPM 8850, HB 8850). Three lecture hours and a one-hour laboratory session per week. NOTE: No student can be awarded more than one course credit among HB 8850, VPM 8850, CS 3220 and BIO 3220.
PREREQUISITE: Computer Science 3220L (concurrent with taking this course)
3 hours credit
CS-3220L - Computer Science 3220 Lab
PREREQUISITE: Computer Science 3220 (concurrent with taking this course)
CS-3320 - THEORY OF COMPUTING
3 hours credit
CS-3420 - COMPUTER COMMUNICATIONS This course introduces the basic principles of modern computer communication: protocols, architectures and standards. Topics include layered architectures, data transmission, error and flow control, medium access, routing, congestion control and common internet application protocols. Three lecture hours per week
PREREQUISITE: Computer Science 2520 and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-3520 - OPERATING SYSTEMS This course introduces the student to the major concepts of modern operating systems. Topics covered include: process management, memory management, file systems, device management and security. Three lecture hours per week
PREREQUISITE: Computer Science 2520, Computer Science 2610, and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-3610 - ANALYSIS AND DESIGN OF ALGORITHMS This course, which introduces the study of algorithm design and measures of efficiency, is a continuation of CS 2610. Topics include algorithm complexity and analysis; techniques such as divide and conquer, greedy and dynamic programming; searching and sorting algorithms; graph algorithms; text processing; efficient algorithms for several common computer science problems and NP-completeness. Three lecture hours per week
PREREQUISITE: Computer Science 2610 and Math 2420 (prior to taking this course)
3 hours credit
CS-3620 - SOFTWARE DESIGN AND ARCHITECTURE This course examines the principles and best practices in object-oriented (OO) software design. Topics include a review of foundational OO concepts, OO design principles, classic design patterns, and software architectures. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3710 - DATABASE SYSTEMS This course introduces the fundamental concepts necessary for the design, use and implementation of database systems. Topics discussed include logical and physical organization of data, database models, design theory, data definition and manipulation languages, constraints, views, and embedding database languages in general programming languages. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3840 - TECHNOLOGY MANAGEMENT & ENTREPRENEURSHIP This course provides an overview on how to start and sustain a technology-oriented company. Topics discussed will include the role of technology in society, intellectual property, patents, business plans, financial planning, sources of capital, business structure, liability, tax implications, sales, marketing, operational and human resource management. This course will be taught using problem-based and experiential learning strategies with involvement from real life entrepreneurs as motivators and facilitators. (Cross-listed with Engineering 4430. Three lecture hours per week.
PREREQUISITE: Computer Science 2520, Computer Science 2620, and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-4060 - CLOUD COMPUTING This course examines: the critical technology trends that are enabling cloud computing, the architecture and the design of existing deployments, the services and the applications they offer, and the challenges that need to be addressed to help cloud computing to reach its full potential. The format of this course will be a mix of lectures, seminar-style discussions, and student presentations. Three lecture hours per week
PREREQUISITE: Computer Science 2060 (prior to taking this course)
3 hours credit
CS-4110 - ARTIFICIAL INTELLIGENCE AND AUTOMATED REASONING This course introduces general problem-solving methods associated with automated reasoning and simulated intelligence. Topics include problem abstraction, state space heuristic search theory, pathfinding, flocking behaviour, knowledge representation, propositional logic, reasoning with uncertainty, machine learning and connectionism. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-4120 - MACHINE LEARNING AND DATA MINING Machine learning is the study of mechanisms for acquiring knowledge from large data sets. This course examines techniques for detecting patterns in sets of uncategorized data. Supervised and unsupervised learning techniques are studied, with particular application to real-world data. Three lecture hours per week
PREREQUISITE: Computer Science 3710 and Statistics 2210 (prior to taking this course)
3 hours credit
CS-4230 - PHYSICS OF GAMING
3 hours credit
CS-4350 - COMPUTER GRAPHICS PROGRAMMING This course introduces the student to the principles and tools of applied graphics programming including graphical systems, input and interaction, object modeling, transformations, hidden surface removal, and shading and lighting models. Languages, graphics libraries and toolkits, and video game engines are introduced, as well as relevant graphics standards. Three lecture hours per week
PREREQUISITE: Computer Science 2620 and Math 2610 (prior to taking this course)
3 hours credit
CS-4360 - ADVANCED COMPUTER GRAPHICS PROGRAMMING This course builds on the computer graphics programming concepts introduced in CS 4350. Students are given a deeper understanding of the components of the 3D graphics pipeline, and how they are used in modern graphical applications. Topics include advanced texture mapping, practical uses of vertex and pixel shaders, screen post-processing, particle systems, and graphics engine design. Three lecture hours per week
PREREQUISITE: Computer Science 4350 (prior to taking this course)
3 hours credit
CS-4440 - DATA SCIENCE Data science is an interdisciplinary and emerging field where techniques from several areas are used to solve problems using data. This course provides an overview and hands-on training in data science, where students will learn to combine tools and techniques from computer science, statistics, data visualization and the social sciences. The course will focus on: 1) the process of moving from data collection to product, 2) tools for preparing, manipulating and analyzing data sets (big and small), 3) statistical modelling and machine learning, and 4) real world challenges. Three lecture hours per week
PREREQUISITE: Computer Science 3710 and Statistics 2210 (prior to taking this course)
3 hours credit
CS-4610 - WIRELESS SENSOR NETWORKS This course is an introduction to Wireless Sensor Networks. It includes the following topics: single-node architecture, wireless sensor network architecture, physical layer, MAC protocols, link-layer protocols, naming and addressing, time synchronization, localization and positioning, topology control, routing protocols, transport layer, and quality of service. Three lecture hours per week
PREREQUISITE: Computer Science 2520 and Computer Science 2610 (prior to taking this course)
3 hours credit
CS-4650 - VIDEO-GAME ARCHITECTURE This programming-driven course aims to explore the various systems that comprise a typical video-game project, including event systems, state machines, rendering, scripting and AI programming. Students will implement these components throughout the course with the end goal of building a small game. Three lectures hours per week
PREREQUISITE: Computer Science 4360
3 hours credit
CS-4720 - COMPILER DESIGN This is a first course in compiler design. The course covers: compilation phases, lexical analysis, parsing, scope rules, block structure, symbol tables, run-time heap and stack management, code generation, pre-processing, compiler-compilers, and translation systems. Three lecture hours per week
PREREQUISITE: MCS 3320 (prior to taking this course)
3 hours credit
CS-4810 - SOFTWARE ENGINEERING This course emphasizes the theory, methods and tools employed in developing medium to large-scale software which is usable, efficient, maintainable, and dependable. Project management is a major focus. Topics include traditional and agile process models, project costing, scheduling, team organization and management, requirements modelling/specification, software design, software verification and testing, and re-engineering. Three lecture hours per week. Restriction: Student must have fourth year standing in Computer Science
3 hours credit
CS-4820 - SOFTWARE SYSTEMS DEVELOPMENT PROJECT In this course, students propose, complete and present a significant software project in a group setting using the system development skills learned in CS 4810. The course applies object-oriented design principles through the use of UML. Students are encouraged to select (with the consent of the instructor) a project with a real-world client. One lecture hour per week plus significant project time
PREREQUISITE: Computer Science 4810 (May be taken concurrently in exceptional circumstances) (prior to taking this course)
3 hours credit
CS-4830 - VIDEO GAME PROGRAMMING PROJECT In this course, students work as a group to develop a single design into a fully functioning video game. This course applies the project management skills learned in CS 4810 to the development of a professional quality video game based upon a single design and prototype emerging from CS 3110. One lecture hour per week plus significant project time. Semester hours of credit: 6
PREREQUISITE: Computer Science 3110, Computer Science 4810 and enrolment in the Computer Science with Video Game Programming major. (prior to taking this course)
6 hours credit
CS-4840 - PROTOTYPE SYSTEMS DEVELOPMENT This course is for student teams who wish to develop an early prototype of a product which they hope to pitch to an external start-up accelerator program post-graduation. Student teams may be inter-disciplinary, but students must register for this course (or its equivalent) within their home school/department. Entry into the course is dependent upon a pitch for the product being judged as economically viable by a team of project mentors. Pitches are made at the conclusion of CS 3840. One lecture hour per week plus significant project time. Semester hours of credit: 6
PREREQUISITE: Computer Science 3840 and permission of the instructor (prior to taking this course)
6 hours credit
CS-ELEC - COMPUTER SCIENCE ELECTIVE
3 hours credit
CS-ELEC1 - COMP. SCI. ELECTIVE 1000 LEVEL
3 hours credit
CS-ELEC2 - COMP. SCI. ELECTIVE 2000 LEVEL
3 hours credit
CS-ELEC3 - COMP SCI ELECTIVE
3 hours credit
CS-ELEC4 - COMP SCI ELECTIVE 4000 LEVEL
3 hours credit

Applied Mathematical Sciences (AMS) Courses

AMS-2160 - MATHEMATICS OF FINANCE This first course in the mathematics of finance includes topics such as measurement of interest; annuities and perpetuities; amortization and sinking funds; rates of return; bonds and related securities; life insurance. Three lecture hours a week
PREREQUISITE: Math 1910 (prior to taking this course)
3 hours credit
AMS-2160L - Mathematics of Finance Lab
PREREQUISITE: AMS 2160 (concurrent with taking this course)
AMS-2400 - FINANCIAL MATHEMATICS & INVESTMENTS Advanced topics of Theory of Interest as initially covered in AMS 2160 including time value of money, annuities, loans, bonds, general cash flows, portfolios and immunization concepts, as well as an introduction to capital markets, analysis of equity and fixed income investments, and an introduction to derivative securities including futures, forwards, swaps and options. Three lecture hours plus a two hour lab per week
PREREQUISITE: AMS 2400L (concurrent with taking this course)
3 hours credit
AMS-2400L - Financial Mathematics and Investments Lab
PREREQUISITE: AMS 2400 (concurrent with taking this course)
AMS-2400T - AMS 2400 TUTORIAL
PREREQUISITE: AMS-2400; (concurrent with taking this course)
AMS-2410 - FINANCIAL ECONOMICS I Introduction to mathematical techniques used to price and hedge derivative securities in modern finance. Modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes. Applications of derivatives in practice will also be discussed. Three lecture hours a week
PREREQUISITE: AMS 2410 Lab (concurrent with taking this course)
3 hours credit
AMS-2410L - Financial Economics Lab I
PREREQUISITE: AMS 2410 (concurrent with taking this course)
AMS-2510 - ACTUARIAL SCIENCE I This course will explore the future lifetime random variable, probability and survival functions, force of mortality; complete and curtate expectation of life, and Makeham and Gompertz mortality laws. Other topics will include: Life tables, characteristics of population and insurance life tables, selection, and fractional age assumptions. Life insurance payments and annuity payments: Present value random variables; expected present values; higher moments; actuarial notation, annual, 1/mthly and continuous cases, relationships between insurance and annuity functions. Premiums, expense loadings, present value of future loss random variables and distribution, net and gross cases, the equivalence principle and portfolio percentile principle will also be discussed. Three lecture hours a week
PREREQUISITE: AMS-2510L (concurrent with taking this course)
3 hours credit
AMS-2510L - Actuarial Science Lab 1
PREREQUISITE: AMS 2510 (concurrent with taking this course)
AMS-2860 - ACTUARIAL MATHEMATICS LAB I This lab features problem-solving sessions for the professional examination on financial mathematics of the Society of Actuaries and the Casualty Actuarial Society. Semester hours of credit: 1
PREREQUISITE: AMS 2160 (prior to taking this course)
3 hours credit
AMS-2940 - OPTIMIZATION An introduction to the methods and applications of linear programming. Topics include linear programming formulations, the simplex method, duality and sensitivity analysis, and integer programming basics. Applications to transportation, resource allocation and scheduling problems will be examined. Software will be used to illustrate topics and applications. Three lecture hours per week
PREREQUISITE: MATH 2610 (prior to taking this course)
3 hours credit
AMS-3160 - GAME THEORY The course covers the fundamentals of game theory and its applications to the modeling of competition and cooperation in business, economics, biology and society. It will include two-person games in strategic form and Nash equilibria, extensive form games, including multi-stage games, coalition games and the core Bayesian games, mechanism design and auctions. PREREQUISITES: Math 192, Math 242 and Stat 222 Three lecture hours per week
PREREQUISITE: Math 1920, Math 2420 and Statistics 2220 (prior to taking this course)
3 hours credit
AMS-3310 - ADVANCED CORPORATE FINANCE FOR ACTUARIES This course covers various advanced topics in corporate finance, with emphasis on theories of corporate incentives and asymmetric information. Illustrative applications using cases are provided. Topics include: capital budgeting, real options, investment decision using Markowitz and utility theory, the Capital Asset Pricing Model, Arbitrage Pricing Theory, market efficiency and capital structure and dividend policy. Other topics may include time value of money, capital budgeting, cost of capital, security issuance, capital structure, payout policy and dividends, short-term finance, and risk management. Where suitable, topics are treated from a mathematical and quantitative perspective. Three lecture hours per week
PREREQUISITE: AMS 2400 and BUS 2310 (prior to taking this course)
3 hours credit
AMS-3410 - FINANCIAL ECONOMICS II This course will discuss advanced mathematical techniques used to price and hedge derivative securities in modern finance. Topics include: modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes. Students will also have the opportunity to apply these derivatives in practice. Three lecture hours per week
PREREQUISITE: AMS 3410L (concurrent with taking this course)
3 hours credit
AMS-3410L - Financial Economics II Lab
PREREQUISITE: AMS 3410 (concurrent with taking this course)
AMS-3510 - ACTUARIAL SCIENCE II This course will discuss: policy values, annual, 1/mthly and continuous cases, Thiele's equation, policy alterations, modified policies and multiple state models. Other topics will include applications in life contingencies, assumptions, Kolmogorov equations, premiums, policy values, multiple decrement models, Joint Life Models, Valuation of insurance benefits on joint lives, and dependent and independent cases. Three lecture hours per week
PREREQUISITE: AMS-3510L (concurrent with taking this course)
3 hours credit
AMS-3510L - Actuarial Science II Lab
PREREQUISITE: AMS 3510 (concurrent with taking this course)
AMS-3730 - ADVANCED INSURANCE AND ACTUARIAL PRACTICES This course is a study of cash flow projection methods for pricing, reserving and profit testing. Topics include: deterministic, stochastic and stress testing; pricing and risk management of embedded options in insurance products; mortality and maturity guarantees for equity-linked life insurance. Three lecture hours per week
PREREQUISITE: AMS 3510 (prior to taking this course)
3 hours credit
AMS-3770 - COMBINATORIAL OPTIMIZATION In this course, various algorithms will be considered, including minimum spanning tree, shortest path, maximum flow, and maximum matching. The links with linear and integer programming will also be considered, with particular attention to duality. Three lecture hours per week
PREREQUISITE: MATH 2420 and AMS 2940 (prior to taking this course)
3 hours credit
AMS-3910 - MATHEMATICAL MODELLING This course studies the process of mathematical modeling, namely, formulating a "real-world" problem in mathematical terms, solving the resulting mathematical problem, and interpreting the solution. Major topics include the modeling of optimization problems (using the techniques of linear programming), and deterministic and probabilistic dynamical processes (with models formulated as differential and difference equations). Applications are taken from science, business and other areas, according to class interest. Three lecture hours per week
PREREQUISITE: A statistics course (prior to taking this course)
3 hours credit
AMS-4080 - FINANCIAL MATHEMATICS II This course explores calculus in a stochastic environment. Topics include: random functions, derivative, chain rule, integral, integration by parts, partial derivatives, pricing forwards and options. Ito's lemma and financial applications, Hull-White, Artzner-Heath, and Brennan-Schwartz models Martingales, pricing methodology, and risk-neutral probability will also be discussed. Three lecture hours per week
PREREQUISITE: MATH 2610 and AMS 3410 (prior to taking this course)
3 hours credit
AMS-4090 - FINANCIAL MATHEMATICS III This course discusses forming risk-free portfolios, the Black-Scholes partial differential equation, constant dividend case, exotic options, drift adjustment, and equivalent martingale measures. Topics also include: Cox-Ross-Rubinstein, Merton and Vasicek's models, stochastic optimization, Hamilton-Jacobi-Bellman equation, and application to American options. Three lecture hours per week
PREREQUISITE: AMS 4080 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4540 - LOSS MODELS I This course explores models for loss severity, parametric models, effect of policy modifications, and tail behaviour. Topics also include: models for loss frequency: (a, b, 0), (a, b, 1), mixed Poisson models; compound Poisson models, Aggregate claims models: moments and moment generating function: recursion and Classical ruin theory. Three lecture hours per week
PREREQUISITE: AMS 3510 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4550 - LOSS MODELS II This course is a study of the mathematics of survival models and includes some examples of parametric survival models. Topics include: tabular survival models, estimates from complete and incomplete data samples, parametric survival models, and determining the optimal parameters. Maximum likelihood estimators, derivation and properties, product limit estimators, Kaplan-Meier and Nelson-Aalen, credibility theory: limited fluctuation; Bayesian; Buhlmann; Buhlmann-Straub; empirical Bayes parameter estimation; statistical inference for loss models; maximum likelihood estimation; the effect of policy modifications; and model selection will also be discussed. Three lecture hours per week
PREREQUISITE: AMS 4540 (prior to taking this course)
3 hours credit
AMS-4580 - CREDIBILITY THEORY This course is a credibility approach to inference for heterogeneous data; classical, regression and Bayesian models; with illustrations from insurance data. Three lecture hours per week
PREREQUISITE: AMS 3510 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4680 - NONLINEAR OPTIMIZATION This course is a study of unconstrained optimization, optimality conditions (necessary, sufficient and Karush-Kuhn-Tucker), penalty functions, convex functions, and convex programming. Three lecture hours per week
PREREQUISITE: MATH 2910 and AMS 2940 (prior to taking this course)
3 hours credit
AMS-4780 - QUANTITATIVE RISK MANAGEMENT This course is an introduction to financial risk management. Topics include: risk measures, modeling for multivariate distributions and copulas, market, credit and operational risk. Advanced topics in quantitative risk management will also be discussed. Three lecture hours per week
PREREQUISITE: AMS 3310 (prior to taking this course)
3 hours credit
AMS-ELEC1 - APP. MATH ELECTIVE 1000 LEVEL
3 hours credit
AMS-ELEC2 - APP. MATH ELECTIVE 2000 LEVEL
3 hours credit
AMS-ELEC3 - APP. MATH ELECTIVE 3000 LEVEL
3 hours credit
AMS-ELEC4 - APP. MATH ELECTIVE 4000 LEVEL
3 hours credit

Mathematical and Computational Sciences (MCS) Courses

MCS-2010 - MAPLE TECHNOLOGY LAB An introduction to the software package MAPLE. Topics include the basic functions and commands, mathematical problem solving using MAPLE, and programming in the internal MAPLE language. Two lab hours per week for 6 weeks. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Math 1920 (prior to taking this course)
1 hour credit
MCS-2020 - MATLAB TECHNOLOGY LAB An introduction to the software package Matlab. Topics include the basic functions and commands, programming and problem-solving using Matlab. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Math 2610 (prior to taking this course)
1 hour credit
MCS-2030 - R TECHNOLOGY LAB An introduction to the software package R. Topics include the basic functions and commands, programming and problem-solving using R. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Statistics 2220 (prior to taking this course)
1 hour credit
MCS-2040 - VISUAL BASIC IN EXCEL TECHNOLOGY LAB An introduction to the software package Excel and Visual Basic in the Excel environment. Topics include the basic functions and commands, programming and problem-solving using Excel and Visual Basic. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and AMS 2400 (prior to taking this course)
1 hour credit
MCS-2050 - GGY AXIS TECHNOLOGY LAB An introduction to the software package GGY AXIS. Topics include the basic functions and commands, programming and problem-solving using GGY AXIS. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and AMS 2510 (prior to taking this course)
1 hour credit
MCS-2840 - CO-OP CAREER SKILLS I This course offers introductory career skills training to prepare co-op students for their first work term. Students are assessed on a pass/fail basis. Cross-listed with Business (cf. Business 2920) Semester hours of credit: 0 Restriction: Student must be admitted into the Mathematical and Computational Sciences Co-operative Education Program
MCS-2850 - CO-OP WORK TERM I This course is a co-op students' first work term. A work term report related to a technical problem/issue within the organization where the student is working is required. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 2840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-3050 - TUTORING IN MATHEMATICAL AND COMPUTATIONAL SCIENCES Students are introduced to techniques for facilitating learning in the Mathematical and Computational Sciences, and then put these techniques into practice by mediating student group learning either in introductory Mathematical and Computational Sciences courses, Mathematical and Computational Science Help Centre or in outreach programs to High Schools. Semester hours of credit: 1
PREREQUISITE: At least 36 credit hours completed in courses in the School of Mathematical and Computational Sciences (prior to taking this course)
1 hour credit
MCS-3320 - THEORY OF COMPUTING This course introduces automata theory, formal languages and computability. Topics include: finite automata; regular expressions; regular, context-free, and context-sensitive languages; computability models; algorithmic decidable and undecidable problems. Three lecture hours per week
PREREQUISITE: Computer Science 2610 and Math 2420 (prior to taking this course)
3 hours credit
MCS-3500 - QUANTUM INFORMATION Introduction to quantum information science; the field of studying, storing, processing and communicating information using quantum systems. Topic include quantum mechanics for Qubit Systems, foundations of Quantum Computing, algorithms, communication and cryptography. Three lecture hours per week.
PREREQUISITE: Math 2620 (prior to taking this course)
3 hours credit
MCS-3840 - CO-OP CAREER SKILLS II This course offers career skills training to strengthen co-op students' readiness for their second work term. Students are assessed on a pass/fail basis. Cross-listed with Business (cf. Business 3920) Semester hours of credit: 0
PREREQUISITE: MCS 2850 (prior to taking this course)
MCS-3850 - CO-OP WORK TERM II This course is a co-op students' second work term. Students will submit a report summarizing their work term achievements. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 3840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-3920 - NUMERICAL ANALYSIS Approximate solution of equations, various interpolative or iterative methods, especially Newton's; convergence tests and rates of convergence; roundoff and truncation errors; propagation of error in calculations; interpolating polynomials; Gauss-Jordan and other methods for simultaneous linear equations; inversion of matrices; determinants and eigenvalues; simultaneous nonlinear equations; evaluation of definite integrals; approximate derivatives; initial-value ordinary differential equations; least-squares curve fitting. Three lecture hours per week
PREREQUISITE: Math 3010 and Computer Science 1510 or equivalent (prior to taking this course)
3 hours credit
MCS-3950 - This course provides students with an opportunity to pursue special topics in Mathematical and Computational Science. Content varies from year to year. Three lecture hours per week. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-4210 - PROFESSIONAL COMMUNICATION AND PRACTICE This course aims to build students' oral and written communications skills, and to prepare them for a professional environment. Using examples from their discipline, students will focus on such aspects as description of processes, presentation of data, extended abstracts, correct use of terminology, and sensitivity to language and tone. Discussions of topics relevant to the professional Mathematical and Computational Scientist are also a key part of the course. Three hours per week
PREREQUISITE: At least 36 credit hours completed in the School of Mathematical and Computational Sciences (prior to taking this course)
3 hours credit
MCS-4420 - CRYPTOGRAPHY AND CODES This course is a study of classic and modern methods of encryption, applications to public-key ciphers, random number generators, attacks on encryption systems, error correcting codes; and computational number theory. Three lecture hours per week
PREREQUISITE: Math 3420 (prior to taking this course)
3 hours credit
MCS-4840 - CO-OP CAREER SKILLS III This course offers career skills training to strengthen co-op students' readiness for their third work term. Students are assessed on a pass/fail basis. Cross-listed with Business 4920 and Physics 4840 Semester hours of credit: 0
PREREQUISITE: MCS 3850 (prior to taking this course)
MCS-4850 - CO-OP WORK TERM III This course is a co-op students' third work term. Students will submit a report summarizing their work term achievements. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 4840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-4860 - CO-OP WORK TERM IV This optional work term is only available to co-op students in the School of Mathematical and Computational Sciences, who elect for a fourth work term. The goal is to add further value for the student, integrating classroom theory with professional skills acquired during the work term. Semester hours of credit: 0
PREREQUISITE: MCS 4850 (prior to taking this course)
MCS-4900 - HONOURS PROJECT This course is intended to give research experience to students planning to pursue graduate studies in an area of Mathematical and Computational Sciences, or planning a career where research experience would be an asset. It provides students with the opportunity to do an independent research project on Mathematical or Computational Sciences topic, under the supervision of a faculty member. Some or all of the work may be done during the summer months. Semester hours of credit: 6 Restriction: Student must be accepted to an Honours program in the School of Mathematical and Computational Sciences
6 hours credit
MCS-4910 - DIRECTED STUDIES IN MATHEMATICAL AND COMPUTATIONAL SCIENCES These courses are designed and recommended for students in the Mathematical and Computational Sciences to encourage independent initiative and study. Reading and research will be conducted in one or more specialized areas. (See Academic Regulation 9 for Regulations Governing Directed Studies.) Three semester hours of credit. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-4950 - ADVANCED TOPICS IN MATHEMATICAL AND COMPUTATIONAL SCIENCES This course provides students with an opportunity to pursue advanced topics in Mathematical and Computational Sciences. Content varies from year to year but is always at a fourth-year level. Prospective students should contact the School of Mathematical and Computational Sciences for a more detailed description of any particular year's offering. Three lecture hours per week. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-ELEC1 - MCS ELECTIVE 1000 LEVEL
3 hours credit
MCS-ELEC2 - MCS ELECTIVE 2000 LEVEL
3 hours credit
MCS-ELEC3 - MCS ELECTIVE 3000 LEVEL
3 hours credit
MCS-ELEC4 - MCS ELECTIVE 4000 LEVEL
3 hours credit

Information Technology (IT) Courses

IT-1210 - INTRODUCTION TO COM PROGRAM
3 hours credit
IT-1320 - This course will address traditional storytelling and the challenges of interactive narrative. Students will develop a solid understanding of traditional narrative theory as well as experimental approaches to storytelling in literature, theatre and film with relevance to game development. Three lecture hours per week
3 hours credit
IT-3710 - This course is an introduction to relational database concepts and design for non-computer science majors. Topics include the logical and physical organization of data, database models, design theory, data definition and manipulation languages, constraints, views, database security, data warehousing and data mining.
3 hours credit
IT-ELEC1 - INFO TECH ELECTIVE 1000 LEVEL
3 hours credit
IT-ELEC2 - INFO TECH ELECTIVE 2000 LEVEL
3 hours credit
IT-ELEC3 - INFO TECH ELECTIVE 3000 LEVEL
3 hours credit
IT-ELEC4 - INFO TECH ELECTIVE 4000 LEVEL
3 hours credit
People

Overview

The School of Mathematical and Computational Sciences (SMCS) is built on a strong foundation of core Mathematics and Computer Science programs that have existed at UPEI for many years. The SMCS is unique in Atlantic Canada for offering a comprehensive suite of majors in the quantitative disciplines.

Mathematical and computational sciences are experiencing a “boom”, as many industries and sectors need people with the skills to manage, analyze, and extract useful information from data. This is what mathematicians, statisticians, and computer scientists are trained to do. Analytics (sometimes called “data science”) is at the intersection of mathematics, statistics, and computer science, and is the hottest area of job growth right now.

We offer the only complete actuarial degree in Atlantic Canada. The unemployment rate for actuaries in Canada is 0%, and the mid-career average salary is near $100,000. When our program is accredited by the Canadian Institute of Actuaries, UPEI will be one of only 12 universities in Canada with an accredited program in actuarial science.

Visit the "Programs" tab to learn about our degrees.  

Programs

The School of Mathematical and Computational Sciences offers degrees in:


Course code prefixes

In the School of Mathematical and Computational Sciences, there are five course prefixes:

  • MATH – for Mathematics courses
  • STAT – for Statistics courses
  • CS – for Computer Science courses
  • AMS – for Applied Mathematical Sciences courses (mainly Actuarial Science and Financial Mathematics)
  • MCS – for common or interdisciplinary courses in Mathematical and Computational Science

Common requirements across all degree programs in the School of Mathematical and Computational Sciences

COMMON CORE

All degree programs in the School of Mathematical and Computational Sciences are built on a common core of courses that should be completed in the first two years of study. This common core consists of the following courses:

Course Course name Credits
MATH 1910 Single Variable Calculus I 4
MATH 1920 Single Variable Calculus II 4
MATH 2610 Linear Algebra I 3
STAT 2210 Introductory Statistics 3
CS 1910 Computer Science I 3
CS 1920 Computer Science II 3

One of:
UPEI 1010
UPEI 1020
UPEI 1030


Writing Studies
Inquiry Studies
University Studies

3
Total Semester Hours of Credit   23

COMMON BREADTH REQUIREMENT

Students must take at least 15 semester hours of credit in courses outside the School of Mathematical and Computational Sciences (excluding one of the UPEI courses listed above), and of these 15 semester hours of credit, at least 6 must be from Biology, Chemistry or Physics and at least 6 must be from outside the Faculty of Science.

COMMON ADVANCED COURSES

Students in all degree programs in the School of Mathematical and Computational Sciences must complete MCS 4210 Professional Communication and Practice (writing-intensive) and MCS 3050 Tutoring in Mathematical and Computational Sciences. 


REQUIREMENTS FOR A MAJOR IN MATHEMATICS

Mathematics is the study of quantity, structure and space. While mathematics is important in understanding and influencing the physical world around us, mathematics can also be curiosity-driven and enjoyed without the requirement of a particular application. The Bachelor of Science with a major in Mathematics provides students with a solid foundation in both pure and applied mathematics, preparing them for graduate studies and professional programs. Students interested in graduate studies in mathematics should consider the Bachelor of Science with honours in Mathematics.

The Major in Mathematics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910- Multivariable and Vector Calculus 4

MATH 2620 - Linear Algebra II

3
MATH 2720 - Mathematical Reasoning  3

At least one of:  MCS 2010 - MAPLE Technology Lab or  MCS 2020  - Matlab Technology Lab

1
MATH 2420 - Combinatorics I   3
STAT 2220 - Introductory Statistics II 3
MATH 3510 - Real Analysis       3
MATH 3610 - Group Theory     3

At least one of : MATH 3010 - Differential Equations, STAT  3210 - Probability and Mathematical Statistics I or  MATH 3310 - Complex Variables

3

Five electives in the Mathematical and Computational Sciences (at the 2000 level or higher with at least two at the 3000 level or higher)

15
MCS 3050 - Tutoring in Mathematical and Computational Sciences    1
MCS 4210 - Professional Communication and Practice 3
Additional general electives                         52
Total Semester Hours of Credit       120

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REQUIREMENTS FOR A MAJOR IN STATISTICS

Statistics is the practice of collecting and analyzing numerical data, and inferring properties of the whole from a representative sample. The Bachelor of Science with a major in Statistics provides students with the solid foundation in both statistical theory and applied statistics necessary to become a statistician or proceed to more specialized statistical study at the graduate level. Students interested in continuing to work in statistics research should consider the Bachelor of Science with honours in Statistics.

The Major in Statistics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3
MCS 2030 - R Technology Lab 1
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I                 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4550 - Data Analysis and Inference 3
STAT 4240 - Experimental Design 3
STAT 4330 - Time Series I       3
STAT 4110 - Statistical Simulation 3
STAT 4410 - Stochastic Processes 3

Two electives in the Mathematical and Computational Sciences (at the 2000 level or higher)           

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit       120

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REQUIREMENTS FOR A MAJOR IN COMPUTER SCIENCE

Computer Science is a key enabler for innovation and discovery in most fields. It encompasses both theory and practice; theoretical ideas about how information is represented and processed, and practical techniques for creating new software. The School offers options such as co-operative education, a specialization in video game programming, and an Honours degree. Employment prospects are among the highest of any field. Honours graduates are well positioned to pursue graduate studies.

The Major in Computer Science requires a total of 120 semester hours of credit, as described below.  

  Credits
The Common Core 23
CS 1610 - Digital Systems 3
CS 2520 - Computer Organization and Architecture 3
CS 2610 -  Data Structures and Algorithms 3
CS 2620 - Comparative Programming Languages 3
CS 2820 - Programming Practices 3
MATH 2420 - Combinatorics I 3
MCS 3320 - Theory of Computing 3
CS 3420 - Computer Communications         3
CS 3520 - Operating Systems 3
CS 3610 - Analysis and Design of Algorithms             3
CS 3620 - Software Design and Architecture 3
CS 3710 - Database Systems 3
CS 4810 - Software Engineering 3

One of: 

CS 4820 - Software Systems Development Project or 
CS 4840 - Prototype Systems Development            

 

3
6

Two electives in Mathematical and Computational Sciences (at the 2000 level or higher)                          

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives: if CS 4820 taken 45
or if CS 4840 taken 42
Total Semester Hours of Credit    

120

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REQUIREMENTS FOR A MAJOR IN ACTUARIAL SCIENCE

Actuarial Science is the study of risk, usually risk associated with insurance, pension, and investment plans. Actuarial Science uses techniques from mathematics, statistics, business, economics, and finance. The Bachelor of Science with a Major in Actuarial Science prepares students to write the early exams required to become an Actuary. Actuaries are in demand as professionals who develop solutions for complex financial issues. Actuaries have excellent career opportunities following graduation as well as excellent co-op work opportunities during their studies. Read more about what actuaries' do, job prospects, and salaries on our departmental website.

The Major in Actuarial Science requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I 3
STAT 3220 - Probability and Mathematical Statistics II 3
STAT 3240 - Applied Regression Analysis 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning               3
MATH 3010 - Differential Equations 3

At least one of: 

MCS 2020 - Matlab Technology Lab
MCS 2040 - Visual Basic in Excel Technology Lab
OR MCS 2050 - GGY AXIS Technology Lab                    

1
AMS 2160 - Mathematics of Finance 3
AMS 2400 - Financial Mathematics & Investments 3
AMS 2410 - Financial Economics I       3
AMS 3410 - Financial Economics II 3
AMS 2510 - Actuarial Science I 3
AMS 3510 - Actuarial Science II 3
AMS 3310 - Advanced Corporate Finance for Actuaries 3
AMS 3730 - Advanced Insurance and Actuarial Practices 3
AMS 4540 - Loss Models I      3
AMS 4550 - Loss Models II 3
AMS 4580 - Credibility Theory 3
STAT 4110 - Statistical Simulation 3
STAT 4330 - Time Series I       3
STAT 4410 - Stochastic Processes       3
MCS 3920 - Numerical Analysis 3
ECON 1010 - Introductory Microeconomics  3
ECON 1020 - Introductory Macroeconomics 3
ACCT 1010 - Introduction to Accounting 3
BUS 2310 - Corporate Finance 3
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives 10
Total Semester Hours of Credit        120

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REQUIREMENTS FOR A MAJOR IN FINANCIAL MATHEMATICS

Financial Mathematics is the application of mathematical models to finance, usually to analyze markets and pricing. Financial Mathematics uses techniques from mathematics, statistics, business, finance, and economics. The Bachelor of Science in Financial Mathematics provides a solid foundation in Financial Mathematics, leading either to a career in the financial sector or to further training in advanced Financial Mathematics. Financial Mathematicians are in demand as professionals who develop solutions for complex financial issues and they have excellent career opportunities following graduation as well as excellent co-op work opportunities during their studies.

The Major in Financial Mathematics requires a total of 120 semester hours of credit, as described below:

  Credit Hours
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning               3
STAT 2220 - Introductory Statistics II 3
STAT 3210 - Probability and Mathematical Statistics I              3
STAT 3220 - Probability and Mathematical Statistics II             3
STAT 3240 - Applied Regression Analysis 3

At least one of: 

MCS 2020 - Matlab Technology Lab
MCS 2030 - R Technology Lab
OR MCS 2040 - Visual Basic in Excel Technology Lab

1
AMS 2160 - Mathematics of Finance 3
AMS 2400 - Financial Mathematics & Investments 3
AMS 2410 - Financial Economics I 3
AMS 3410 - Financial Economics II 3
AMS 4080 - Financial Mathematics II 3
AMS 4090 - Financial Mathematics III               3
AMS 4780 - Quantitative Risk Management 3
AMS 3910 - Mathematical Modelling 3
AMS 3310 - Advanced Corporate Finance for Actuaries 3
MATH 3010 - Differential Equations 3
MATH 3510 - Real Analysis  3
MATH 4710 - Partial Differential Equations 3
STAT 4330 - Time Series I       3

At least one of:

STAT 4410 - Stochastic Processes
OR MATH - 3920 Numerical Analysis

3
ECON 1010 - Introductory Microeconomics  3
ECON 1020 - Introductory Macroeconomics 3

At least one of:

ECON 2510 - Money and Financial Institutions
OR ECON 4050 - Financial Economics

3
ACCT 1010 - Introduction to Accounting           3
BUS 2310 - Corporate Finance 3

At least one of: 

BUS 3330 - Integrated Cases in Corporate Finance
BUS 3660 - Entrepreneurial Finance
BUS 4210 - Personal Finance
BUS 4390 - International Finance
OR BUS 4820 - International Strategy and Finance     

3
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives         10
Total Semester Hours of Credit 120

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REQUIREMENTS FOR A MAJOR IN ANALYTICS

(Specialization in Data Analytics)

Analytics is situated at the confluence of statistics, computer science and mathematics all centered on finding, interpreting and presenting meaningful patterns in data. We offer a Bachelor of Science in Analytics with specialization in either Data Analytics or Business Analytics, with co-operative education options available in both specializations. As data increasingly pervades our lives, graduates in Analytics are in high demand across a broad spectrum of fields including government, business and technology.

The Major in Analytics with a specialization in Data Analytics requires a total of 120 semester hours of credit, as described below: 

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3

At least one of: 

MCS 2010 - MAPLE Technology Lab
MCS 2020 - Matlab Technology Lab
OR MCS 2030 - R Technology Lab       

1
MATH 2420 -  Combinatorics I 3
MATH 3430 - Combinatorics II 3
AMS 2940 - Optimization       3
AMS 3770 - Combinatorial Optimization 3
AMS 3910 - Mathematical Modelling 3
MATH 3010 - Differential Equations 3
MATH 3610 - Group Theory     3
STAT 3210 - Probability and Mathematical Statistics I 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4550 - Data Analysis and Inference 3
STAT 4660 - Data Visualization and Mining 3
CS 2610 - Data Structures and Algorithms 3
CS-2910 - Computer Science III 3
CS 3710 - Database Systems 3
CS 3610 - Analysis and Design of Algorithms             3
CS 4120 - Machine Learning 3
CS 4440 - Data Science 3

Two  electives in Mathematical or Computational Sciences (at the 2000 level or higher)

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences    1
MCS 4210 - Professional Communication and Practice             3
Additional general electives 19
Total Semester Hours of Credit      120

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REQUIREMENTS FOR A MAJOR IN ANALYTICS

(Specialization in Business Analytics)

The Major in Analytics with a specialization in Business Analytics requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus              4
STAT 2220 - Introductory Statistics II                 3
MATH 2620 - Linear Algebra II                3
MATH 2720 - Mathematical Reasoning  3

At least one of:

MCS 2010 - MAPLE Technology Lab
MCS 2020 - Matlab Technology Lab 
OR MCS 2030 - R Technology Lab         

1
MATH 2420 - Combinatorics I 3
MATH 3430 - Combinatorics II 3
AMS 2940 - Optimization       3
AMS 3770 - Combinatorial Optimization 3
AMS 3910 - Mathematical Modelling 3
MATH 3010 - Differential Equations 3
STAT 3210 - Probability and Mathematical Statistics I                 3
STAT 3220 - Probability and Mathematical Statistics II               3
STAT 3240 - Applied Regression Analysis 3
STAT 4660 - Data Visualization and Mining 3

Two electives in the Mathematical and Computational Sciences (at the 3000 level or higher)

6
CS 2610 - Data Structures and Algorithms 3
CS 2910 - Computer Science III 3
CS 3710 - Database Systems 3
ACCT 1010 - Introduction to Financial Accounting 3
BUS 1410 - Marketing 3
BUS 1710 - Organizational Behaviour 3

At least five of: 

ACCT 2210 - Managerial Accounting
BUS 2650 - Introduction to Entrepreneurship
BUS 2880 - Research and Evidence-Based Management
BUS 2720 - Human Resource Management
BUS 3010 - Business Law
BUS 3330 - Integrated Cases in Corporate Finance
BUS 3510 - Operations Management
BUS 3710 - Entrepreneurship and New Ventures
BUS 4650 - Project Management
OR BUS 4880 - Developing Management Skills

15
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice             3
Additional general electives 10
Total Semester Hours of Credit       120

Note: Students who complete the Major in Analytics with a specialization in Business Analytics and obtain grades of at least 60% in seven of the Business courses can also obtain a Certificate in Business.

 

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REQUIREMENTS FOR A MAJOR IN MATHEMATICS WITH ENGINEERING

The specialization augments the Mathematics major with Engineering courses offered through UPEI’s School of Sustainable Design Engineering. The Bachelor of Science in Mathematics with Engineering provides a foundational Engineering program combined with more advanced mathematical training than is received in an Engineering Degree program.

The Major in Mathematics with Engineering requires a total of 120 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910 - Multivariable and Vector Calculus 4
STAT 2220 - Introductory Statistics II 3
MATH 2620 - Linear Algebra II 3
MATH 2720 - Mathematical Reasoning  3
MATH 3010 - Differential Equations 3
MATH 3310 - Complex Variables 3

At least one of:

MATH 3510 - Real Analysis
OR Math 3610 Group Therapy

3

Two electives in Mathematical and Computational Sciences (at the 3000 level or higher)

6
PHYS 1110 and 1120 - General Physics I and II 6
CHEM 1110 and 1120 - General Chemistry I and II 6
ENGN 1210 - Design 1: Engineering Communications 3
ENGN 1220 - Design 2: Engineering Analysis 3
ENGN 1510 - Engineering and the Biosphere 3
ENGN 2210 - Design 3: Engineering Projects I 3
ENGN 2220 - Design 4: Engineering Projects II 3
ENGN 2310 - Strength of Materials 3
ENGN 2340 - Engineering Dynamics 3
ENGN 2610 - Thermofluids I 3
ENGN 2810 - Electrical Circuits I 3
Two electives in Engineering        6
Additional general electives 24
Total Semester Hours of Credit       120

Note: Mathematics with Engineering Majors may substitute ENGN 1320 for CS 1510, and CS 1610 or MCS 3920 for CS 1520.

 

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REQUIREMENTS FOR A MAJOR IN COMPUTER SCIENCE (Specialization in Video Game Programming)

The Major in Computer Science with a specialization in Video Game Programming requires a total of 120 semester hours of credit, as described below.  

  Credits
The Common Core 23
CS 1610 - Digital Systems 3

At least one of:

CS 2120 - Mobile Device Development – iOS 
OR CS 2130 - Mobile Device Development – Android

3
CS 2520 - Computer Organization and Architecture 3
CS 2610 - Data Structures and Algorithms 3
CS 2620 - Comparative Programming Languages 3
CS 2820 - Programming Practices 3
MATH 2420 - Combinatorics I 3
CS 3110 - Video Game Design 3
MCS 3320 - Theory of Computing 3
CS 3420 - Computer Communications         3
CS 3520 - Operating Systems 3
CS 3610 - Analysis and Design of Algorithms 3
CS 3620 - Software Design and Architecture 3
CS 3710 - Database Systems 3
CS 4350 - Computer Graphics Programming 3
CS 4360 -  Advanced Computer Graphics Programming 3

At least two of: 

CS 4060 - Cloud Computing
CS 4120 - Machine Learning
CS 4440 - Data Science
OR CS 4610 - Wireless Sensor Networks

6
CS 4650 - Video Game Architecture 3
CS 4810 - Software Engineering 3
CS 4830 - Video Game Programming Project            6

Two electives in the Mathematical and Computational Sciences (at the 2000 level or higher)

6
MCS 3050 - Tutoring in Mathematical and Computational Sciences 1
MCS 4210 - Professional Communication and Practice 3
Additional general electives 21
Total Semester Hours of Credit 120

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Acceptance to an Honours program

Students in the Mathematics, Statistics and Computer Science programs have an Honours option. Permission of the School of Mathematical and Computational Sciences is required for admission to an Honours program. Students must normally have a minimum average of 70% in all previous courses. Normally, the School expects an average of 75% in all previous Mathematical and Computational Sciences courses. Admission is contingent upon the student finding a project advisor and acceptance by the School of the topic for the Honours project. Students interested in doing Honours are strongly encouraged to consult with the Associate Dean of the School of Mathematical and Computational Sciences as soon as possible, and no later than January 31 of the student’s third year. To receive the Honours designation, in addition to successful completion of the Honours project, normally students must maintain an average of at least 75% in all courses in the School of Mathematical and Computational Sciences.

REQUIREMENTS FOR HONOURS IN MATHEMATICS

The Honours in Mathematics program requires a total of 126 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910  Multivariable and Vector Calculus              4
STAT 2220     Introductory Statistics II                 3
MATH 2620   Linear Algebra II 3
MATH 2720   Mathematical Reasoning  3

At least one of: MCS 2010 - MAPLE Technology Lab OR MCS 2020 - Matlab Technology Lab

1
MATH 2420  Combinatorics I 3
MATH 3510   Real Analysis  3
MATH 3610  Group Theory 3
MATH 3010  Differential Equations 3
STAT   3210  Probability and Mathematical Statistics I 3
MATH 3310  Complex Variables 3
MCS 4900     Honours Project 6

Four electives in the Mathematical and Computational Sciences (at the 2000 level or higher, with at least two at the 4000 level or higher)

12
MCS 3050  Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit    126

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REQUIREMENTS FOR HONOURS IN STATISTICS

The Honours in Statistics program requires a total of 126 semester hours of credit, as described below:

  Credits
The Common Core 23
MATH 2910  Multivariable and Vector Calculus 4
STAT 2220    Introductory Statistics II 3
MATH 2620  Linear Algebra II 3
MATH 2720  Mathematical Reasoning  3
MCS 2030    R Technology Lab 3
STAT 3210  Probability and Mathematical Statistics I                 3
STAT 3220  Probability and Mathematical Statistics II 3
STAT 3240   Applied Regression Analysis 3
STAT 4550  Data Analysis and Inference 3
STAT 4240  Experimental Design       3
STAT 4330  Time Series I       3
STAT 4110   Statistical Simulation 3
STAT 4410   Stochastic Processes 3
MCS 4900   Honours Project 6

Two electives in the Mathematical and Computational Science (at the 3000 level or higher)

6
MCS 3050  Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives         49
Total Semester Hours of Credit 126

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REQUIREMENTS FOR HONOURS IN COMPUTER SCIENCE

The Honours in Computer Science requires a total of 126 semester hours of credit, as described below.  
 

  Credits
The Common Core 23
CS 1610 Digital Systems 3
CS 2520  Computer Organization and Architecture 3
CS 2610   Data Structures and Algorithms 3
CS 2620   Comparative Programming Languages 3
CS 2820   Programming Practices 3
MATH 2420  Combinatorics I 3
MATH 2910  Multivariable Calculus 4
MCS 3320   Theory of Computing 3
CS 3420   Computer Communications 3
CS 3520   Operating Systems 3
CS 3610   Analysis and Design of Algorithms             3
CS 3620   Software Design and Architecture 3
CS 3710   Database Systems 3

At least one of: CS 4110 - Artificial Intelligence and Automated Reasoning OR CS 4120 - Machine Learning

3
CS 4810   Software Engineering 3
MCS 4900  Honours Research Project 6

Four electives in the Mathematical and Computational Sciences (at the 2000 level or higher)

12
MCS 3050 Tutoring in Mathematical and Computational Sciences 1
MCS 4210  Professional Communication and Practice             3
Additional general electives 35
Total Semester Hours of Credit     126

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REQUIREMENTS FOR A MINOR IN MATHEMATICS

Students may obtain a Minor in Mathematics by completing at least 24 semester hours of credit in Mathematics defined as follows:

Math 1910-1920 - Single Variable Calculus I & II 8
Math 2610 - Linear Algebra I 3
Math 2910 - Multivariable and Vector Calculus 4
plus 3 semester hours of credit in Mathematics at the 3000 level or higher, and an additional 6 semester hours of credit of Mathematics at the 2000 level or above 9
Total Semester Hours of Credit 24

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REQUIREMENTS FOR A MINOR IN STATISTICS

Students may obtain a Minor in Statistics by completing at least 23 semester hours of credit in Mathematics and Statistics defined as follows:

MATH 1910-1920 - Single Variable Calculus I  & II 8
STAT 2210-2220 - Introductory Statistics I & II 6
MATH 2610 - Linear Algebra I 3
STAT 3210 -  Probability and Mathematical Statistics I 3
plus 3 semester hours of credit in Statistics at the 3000 level or higher 3
Total Semester Hours of Credit 23

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REQUIREMENTS FOR A MINOR IN COMPUTER SCIENCE

Students may obtain a Minor in Computer Science by completing at least 21 semester hours of credit in Computer Science defined as follows:

CS 1910-1920 - Computer Science I & II  6
CS 2520 - Computer Organization and Architecture  3
CS 2610 - Data Structures and Algorithms  3

plus 3 semester hours of credit in Computer Science at the 3000 level or higher, and an additional 6 semester hours of credit in Computer Science at the 2000 level or higher

9
Total Semester Hours of Credit  21
 

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MATHEMATICAL AND COMPUTATIONAL SCIENCES CO-OP PROGRAM

The Mathematical and Computational Sciences Co-op program is an integrated approach to university education that enables students to alternate academic terms on campus with work terms in relevant and supervised employment. The Co-op program consists of eight academic terms, at least three work terms and a series of professional development workshops and seminars. It is available as an option to full-time students enrolled in Major and Honours programs. Application to the co-op program is made in the student’s second year of study. Students must complete 126 semester hours of credit to graduate with the Co-op designation, and no credit will be given for any Co-op work term course, unless at least three work terms are successfully completed.

See the Co-op Education (Mathematical and Computational Sciences) page for complete program details.

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ADMISSION TO SCIENCE CALCULUS

The First-year Calculus courses for most science students are Math 191 and Math 1920. In addition to Grade XII academic Mathematics (or equivalent), a passing grade on an Assessment Test written during the first week of classes is required as a prerequisite for Math 1910. The Assessment Test covers the standard pre-calculus topics of the High School curriculum (arithmetic, algebra, trigonometry, analytic geometry and the basic theory of functions). This test is of 90 minutes duration and is given during the first week of classes.

Students who do not pass the assessment test may have the option of enrolling in a special section of Math 1910 incorporating additional tutorials reviewing pre-Calculus materials. See the Associate Dean of the School of Mathematical and Computational Sciences for details.


 

Courses

Course code prefixes

In the School of Mathematical and Computational Sciences, there are five course prefixes:

Mathematics (MATH) Courses

MATH-1010 - ELEMENTS OF MATHEMATICS This course provides an introduction to several mathematical topics at the university level, and is intended for students majoring in a discipline other than Mathematical and Computational Sciences, or the Natural Sciences. The course consists of four modules: (1) Sets and Logic, (2) Number Theory, (3) Geometry, (4) Mathematical Systems. NOTE: Credit will not be given jointly for this course and any other 1000-level Mathematics course. Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1110 - FINITE MATHEMATICS This course introduces students to finite mathematical techniques and to mathematical models in business, life and the social sciences. The course begins with an introduction to mathematical models, types of models, and conversion of verbal models to mathematical models. Topics covered include systems of linear equations and matrices, linear inequalities and linear programming, sets, counting and probability. NOTE: Credit for Mathematics 1110 will not be allowed if taken concurrent with or subsequent to Mathematics 2610. Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1120 - CALCULUS FOR THE MANAGERIAL, SOCIAL AND LIFE SCIENCES This course provides an introduction to calculus for students in the managerial, social and life sciences. The main emphasis of the course is the development of techniques of differentiation and integration of algebraic, exponential and logarithmic functions. Applications of derivatives and integrals are also discussed. NOTE: Credit will not be given jointly for this course and Math 1910 Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-1910 - SINGLE VARIABLE CALCULUS I This course is an introduction to differential and integral calculus of functions of a single variable. The course is intended primarily for majors in the Mathematical and Computational Sciences, Engineering and the Physical Sciences, as well as those planning to continue with further Mathematics courses. The concepts of limits, continuity and derivatives are introduced and explored numerically, graphically and analytically. The tools of differential calculus are applied to problems in: related rates; velocity and acceleration; extrema of functions; optimization; curve sketching; and indeterminate forms. The concepts of definite and indefinite integrals are introduced, and the relation between the two integrals is discovered via the Fundamental Theorem of Calculus. Four lecture hours per week Semester hours of credit: 4 Prerequisite: Prerequisite: Grade XII academic Mathematics [and a passing grade on the Assessment Test]
PREREQUISITE: Math-1910T (concurrent with taking this course)
4 hours credit
MATH-1910R - PRE-CALCULUS REVIEW TUTORIAL
MATH-1910T - MATH 1910 TUTORIAL
PREREQUISITE: Math 1910 (concurrent with taking this course)
MATH-1920 - SINGLE VARIABLE CALCULUS II This course is a continuation of integral calculus of functions of a single variable and an introduction to sequences and series. Techniques of integration are studied, including improper integrals and numerical integration, and the tools of integral calculus are used to compute areas, volumes and arc lengths; and are applied to problems in physics and differential equations. Sequences, series, tests for convergence, Taylor series and Taylor polynomials are studied. Four lecture hours per week Semester hours of credit: 4
PREREQUISITE: Math-1920T (concurrent with taking this course)
4 hours credit
MATH-1920T - Math 1920 Tutorial
PREREQUISITE: Mathematics 1920 (concurrent with taking this course)
MATH-2420 - COMBINATORICS I This course offers a survey of topics in discrete mathematics that are essential for students majoring in the Mathematical and Computational Sciences. Topics include: logic, proof techniques such as mathematical induction, recursion, counting methods, and introductory graph theory. Three lecture hours per week
PREREQUISITE: Math 1920 (prior to taking this course)
3 hours credit
MATH-2610 - LINEAR ALGEBRA I This course introduces some of the basic concepts and techniques of linear algebra to students of any major. The emphasis is on the interpretation and development of computational tools. Theory is explained mainly on the basis of two or three-dimensional models. Topics covered are: matrices; determinants; systems of equations; vectors in two and three-dimensional space including dot and cross products, lines, and planes; concepts of linear independence, basis, and dimension explained with examples; linear transformations and their matrices; eigenvectors and eigenvalues. Three lecture hours per week Prerequisite: Grade XII academic Mathematics.
3 hours credit
MATH-2620 - LINEAR ALGEBRA II This course continues MATH 2610 with further concepts and theory of linear algebra. Topics include vector spaces, orthogonality, Gram-Schmidt Process, canonical forms, spectral decompositions, inner product spaces and the projection theorem. Three lecture hours a week
PREREQUISITE: Math 1910 and Math 2610 (prior to taking this course)
3 hours credit
MATH-2720 - MATHEMATICAL REASONING This course provides students with experience in writing mathematical arguments. It covers first-order logic, set theory, relations, and functions. The ideas and proof techniques are considered in the context of various mathematical structures such as partial orders, graphs, number systems, and finite groups. Three lecture hours per week
3 hours credit
MATH-2810 - FOUNDATIONS OF GEOMETRY This course presents an axiomatic base for Euclidean geometry and an insight into the interdependence of the various theorems and axioms of that geometry and non-Euclidean geometries. Topics include: incidence and separation properties for points, lines, planes and space; congruence properties; geometric inequalities; similarity properties; and geometric constructions. Three lecture hours per week
PREREQUISITE: Six credit hours of First Year Mathematics (prior to taking this course)
3 hours credit
MATH-2820 - MATHEMATICAL PHYSICS (FORMERLY 3810) (Please note this course will not be offered until January, 2017) This course is an introduction to some of the mathematical methods commonly used in the physical sciences and engineering, with an emphasis on applications in physics. Topics include: vector analysis in curvilinear coordinates, tensor analysis (with applications in fluid mechanics), introduction to complex variables, Fourier series, calculus of variations and applications. Cross-listed with Physics (cf. Physics 2820) Three hours lecture per week
PREREQUISITE: Math 2910 and either Physics 1120 or Physics 1220 (prior to taking this course)
3 hours credit
MATH-2910 - MULTIVARIABLE AND VECTOR CALCULUS This course continues from Math 1920 and is an introduction to multivariable differentiation and integration and vector calculus. Topics include parametric representation of curves; polar coordinates; vectors; dot and cross products; curves and surfaces in space; calculus of vector-valued functions; functions of several variables; partial differentiation; directional derivatives; tangent planes; local and constrained maxima and minima; double and triple integrals; changes of variables in multiple integrals; vector fields; line and surface integrals; gradient, divergence and curl; Green's, Stokes' and Divergence Theorems. Four lecture hours per week Semester hours of credit: 4
PREREQUISITE: Math 1920 (prior to taking this course)
4 hours credit
MATH-2910T - ADDITIONAL LECTURE
MATH-3010 - DIFFERENTIAL EQUATIONS This course introduces the basic theory of differential equations, considers various techniques for their solution, and provides elementary applications. Topics include linear equations; separable equations; linear independence and Wronskian; second-order equations with constant coefficients; nonhomogeneous equations; applications of first- and second-order equations; Laplace and inverse Laplace transforms, and their application to initial-value problems; series solutions about ordinary and singular points; and Fourier series. Three lecture hours per week
PREREQUISITE: Math 1920 (prior to taking this course)
3 hours credit
MATH-3210 - PROBABILITY AND MATH STATS I
3 hours credit
MATH-3220 - PROBABILITY AND MATH STATS II
3 hours credit
MATH-3240 - APPLIED REGRESSION ANALYSIS
3 hours credit
MATH-3310 - COMPLEX VARIABLES This is a first course in complex variables. The aim is to acquaint students with the elementary complex functions, their properties and derivatives, and with methods of integration. Topics covered include: definition and development of complex numbers as ordered pairs; geometric representation; basic formulas and inequalities involving argument and conjugates; roots of complex numbers, limit, continuity, and derivative; Cauchy Riemann conditions; harmonic functions; properties of trigonometric, hyperbolic, logarithmic, exponential, and inverse trigonometric functions; bilinear transformation; integration; Cauchy Integral Theorem and Formula; residues and poles; Laurent and Taylor's series; and improper integrals. Three lecture hours per week
PREREQUISITE: Math 2910 (prior to taking this course)
3 hours credit
MATH-3420 - NUMBER THEORY This first course in number theory will include the following topics: equivalence of the principles of induction and the well-ordering principle; division algorithm; positional notation and repeating decimals; greatest common divisor; Euclidean Algorithm; Fundamental Theorem of Arithmetic; Pythagorean Triplets; Prime Numbers Theorem; Mersenne and Fermat Numbers; congruences; Euler's Phi-function; Chinese Remainder Theorem; Diophantine Equations; Theorems of Lagrange and Wilson; Quadratic Reciprocity Law of Gauss; Legendre symbol and primitive roots; perfect numbers; multiplicative number- theoretic functions; Moebius inversion. Three lecture hours per week
PREREQUISITE: Six credit hours of Mathematics at the 2000 level or higher (prior to taking this course)
3 hours credit
MATH-3430 - COMBINATORICS II This course continues MATH 2420, with the examination of advanced counting techniques, binomial coefficients, and generating functions. Other topics include relations, partial orders, and Steiner Triple systems. Three lecture hours per week
PREREQUISITE: Math 2420 (prior to taking this course)
3 hours credit
MATH-3510 - REAL ANALYSIS This is a first course in real analysis. Topics include: the reals as a complete ordered field; closed and open sets; Bolzano-Weierstrass and Heine-Borel Theorems; Cauchy Sequences; limits and continuity; derivative; Mean Value Theorem; Riemann Integral; and the Fundamental Theorem of Calculus. Three lecture hours per week
PREREQUISITE: Math 1920 and Math 2720 (prior to taking this course)
3 hours credit
MATH-3520 - REAL ANALYSIS II
3 hours credit
MATH-3610 - GROUP THEORY An introduction to group theory, including: cyclic groups, symmetric groups, subgroups and normal subgroups, Lagrange's theorem, quotient groups and homomorphisms, isomorphism theorems, group actions, Sylow's theorem, simple groups, direct and semidirect products, fundamental theorem on finitely generated Abelian groups. Three lecture hours per week
PREREQUISITE: Math 2720 (prior to taking this course)
3 hours credit
MATH-3710 - GRAPH THEORY This course is an introduction to the ideas, methods, and applications of graph theory. Topics include graph connectivity, graph factors and factorizations, planar graphs, and colourings. Three lecture hours per week
PREREQUISITE: Math 2420 or Math 2720 (prior to taking this course)
3 hours credit
MATH-4020 - POINT-SET TOPOLOGY A first course in topology, covering some review of set theory; cardinal numbers; binary relations; metric spaces, convergence and continuity in metric spaces; topological spaces, bases, sub- spaces; continuity in general; homeomorphism; product spaces; separation axioms; compactness; connectedness. Three lecture hours per week
PREREQUISITE: Math 3510 (prior to taking this course)
3 hours credit
MATH-4520 - MEASURE THEORY AND INTEGRATION A first course in measure theory, covering measure as a generalization of length, outer measure, sigma-algebras, measurability, construction of measures, Lebesgue measure on the real line, measurable functions and the Lebesgue integral. Additional topics may include and convergence theorems, product measures and Fubini Theorem. Three lecture hours per week
PREREQUISITE: Math 3510 (prior to taking this course)
3 hours credit
MATH-4530 - FUNCTIONAL ANALYSIS This first course in functional analysis covers topics like: metric spaces, Banach spaces, function spaces, Hilbert spaces, generalized Fourier series and linear operators. Three lecture hours per week
PREREQUISITE: Math 2620 and Math 3510 (prior to taking this course)
3 hours credit
MATH-4620 - RING AND FIELD THEORY Introduction to ring and field theory, including: polynomial rings, matrix rings, ideals and homomorphisms, quotient rings, Chinese remainder theorem, Euclidean domains, principal ideal domains, unique factorization domains, introduction to module theory, basic theory of field extensions, splitting fields and algebraic closures, finite fields, introduction to Galois theory. Three lecture hours per week
PREREQUISITE: Math 3610 (prior to taking this course)
3 hours credit
MATH-4710 - PARTIAL DIFFERENTIAL EQUATIONS This course is an introduction to the theory and application of partial differential equations. Topics include: first-order equations and characteristic curves; classification of second-order equations as parabolic, hyperbolic or elliptic; Laplace, wave and diffusion equations, and their physical origins; solution using Fourier series; and separation of variables. Three lecture hours per week
PREREQUISITE: Math 2910 and Math 3010 (prior to taking this course)
3 hours credit
MATH-4720 - DYNAMICAL SYSTEMS This course is a study of the long-term qualitative behaviour of solutions of systems of differential or difference equations. Topics include: non-linear systems, linearization, numerical and graphical methods, equilibria, phase space, stability, bifurcations, strange attractors, and chaos. Applications to physics, biology and other sciences are studied. Three lecture hours per week
PREREQUISITE: Math 2610, Math 2910, and Math 3010 (prior to taking this course)
3 hours credit
MATH-ELEC1 - MATH ELECTIVE 1000 LEVEL
3 hours credit
MATH-ELEC2 - MATH ELECTIVE 2000 LEVEL
3 hours credit
MATH-ELEC3 - MATH ELECTIVE 3000 LEVEL
3 hours credit
MATH-ELEC4 - MATH ELECTIVE 4000 LEVEL
3 hours credit

Statistics (STAT) Courses

STAT-2210 - INTRODUCTORY STATISTICS I The main objective of this course is to introduce the basic concepts of descriptive statistics, statistical inference, and the use of statistical software such as MINITAB to students in any discipline. More time is spent on statistical inference than on descriptive statistics. Topics include frequency distributions, descriptive statistics, rules of probability, discrete and continuous probability distributions, random sampling and sampling distributions, confidence intervals, one- and two-tail tests of hypotheses, and correlation and linear regression. NOTE: Credit will not be allowed for Statistics 2210 if a student has received credit for any of the following courses: Business 2510, Education 4810, Psychology 2710 and Sociology 3320. Prerequisite: Grade XII academic Mathematics.
3 hours credit
STAT-2220 - INTRODUCTORY STATISTICS II The course builds upon the knowledge developed in Introductory Statistics I and introduces students to statistical techniques commonly used in research. Topics include linear regression and multiple linear regression, residual analysis, simple ANOVA models, categorical data analysis, simple sampling models, and common distributions (including binomial, Poisson, and exponential). Three lecture hours per week
PREREQUISITE: Statistics 2210 (prior to taking this course)
3 hours credit
STAT-3210 - PROBABILITY AND MATHEMATICAL STATISTICS I This course is an introduction to the theoretical basis of statistics for students who have completed Introductory Statistics. The study concentrates on the mathematical tools required to develop statistical methodology. Topics covered include: probability, continuous and discrete random variables, moment generating functions, multivariate probability distributions and functions of random variables. Three lecture hours per week
PREREQUISITE: Math 2910 and Stat 2220 or permission of the instructor (prior to taking this course)
3 hours credit
STAT-3220 - PROBABILITY AND MATHEMATICAL STATISTICS II This course builds on the mathematical foundation developed in Statistics 3210 and introduces the student to the theory of statistical inference. Topics covered include: sampling distributions and central limit theory, methods of estimation, hypothesis testing, least squares estimation of linear models, and an introduction to Bayesian inference. Three lecture hours per week
PREREQUISITE: Statistics 3210 (prior to taking this course)
3 hours credit
STAT-3240 - APPLIED REGRESSION ANALYSIS This course builds upon the basis of inference studied in Statistics 2210 and provides students with an advanced knowledge of regression techniques. Topics covered are simple and multiple linear regression techniques, matrix notation, the design matrix, model building techniques, residual analysis, and non-linear regression. Three lecture hours per week
PREREQUISITE: Statistics 2210 and Math 2610 (prior to taking this course)
3 hours credit
STAT-4110 - STATISTICAL SIMULATION This course introduces statistical simulation, and its use as a tool to investigate stochastic phenomena and statistical methods. Topics include the building and validation of stochastic simulation models useful in computing, operations research, engineering and science; related design and estimation problems; variance reduction; and the implementation and the analysis of the results. Three lecture hours per week
PREREQUISITE: Statistics 3220 (prior to taking this course)
3 hours credit
STAT-4240 - EXPERIMENTAL DESIGN This course builds upon the basis of inference studied in Statistics 2210 and Statistics 3240 to include statistical techniques commonly used in experimental studies. Students will study topics such as analysis of variance models, hypothesis testing in ANOVA models, randomization, and blocking techniques. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4280 - GENERALIZED LINEAR MODELS This course covers the basic theory, methodology and applications of generalized linear models. Topics include logistic regression, probit regression, binomial regression, Poisson regression, overdispersion, quasi-likelihood, and the exponential family. Three lecture hours per week
PREREQUISITE: Statistics 3220 and Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4330 - TIME SERIES I This course is an introduction to Time Series methods, including: stationary models, trends and seasonality, stochastic Time Series models, autoregressive and moving average processes and an introduction to Time Series forecasting. ARIMA models. Seasonal Time Series and Spectral Analysis are also covered. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4340 - TIME SERIES II This course includes topics from Time Series Econometrics, including Maximum Likelihood and Least Squares Estimation of ARIMA Models and GARCH Models, Wavelets and Financial Models. Non-stationary Time Series, multivariate Time Series and panel cointegration analysis are also covered. Three lecture hours per week
PREREQUISITE: Statistics 4330 (prior to taking this course)
3 hours credit
STAT-4410 - STOCHASTIC PROCESSES This course is an introduction to the branch of probability theory that deals with the analysis of systems that evolve over time. Topics include random walks, Markov chains, Poisson processes, continuous time Markov chains, birth and death processes, exponential models, and applications of Markov chains. Three lecture hours per week
PREREQUISITE: Statistics 3220 (prior to taking this course)
3 hours credit
STAT-4550 - DATA ANALYSIS AND INFERENCE This course is an introduction to data analysis with a focus on regression. Topics include: initial examination of data, correlation, and simple and multiple regression models using least squares. Inference for regression parameters, confidence and prediction intervals, diagnostics and remedial measures interactions and dummy variables, variable selection, least squares estimation and inference for non-linear regression will also be discussed. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-4660 - DATA VISUALIZATION AND MINING This course introduces students to the statistical methods involved in visualization of high dimensional data, including interactive methods directed at exploration and assessment of structure and dependencies in data. Topics include methods for finding groups in data including cluster analysis, dimension reduction methods including multi-dimensional scaling, pattern recognition, and smoothing techniques. Three lecture hours per week
PREREQUISITE: Math 2620, Math 2910, and Statistics 3210 (prior to taking this course)
3 hours credit
STAT-4740 - MULTIVARIATE ANALYSIS This course deals with the statistics of observation and analysis of more than one output variable. Topics include estimation and hypothesis testing for multivariate normal data, principal component analysis and factor analysis, discriminant analysis, cluster analysis, and correspondence analysis. Three lecture hours per week
PREREQUISITE: Statistics 3240 (prior to taking this course)
3 hours credit
STAT-ELEC1 - STATISTICS ELECTIVE 1000 LEVEL
3 hours credit
STAT-ELEC2 - STATISTICS ELECTIVE 2000 LEVEL
3 hours credit
STAT-ELEC3 - STATISTICS ELECTIVE 3000 LEVEL
3 hours credit
STAT-ELEC4 - STATISTICS ELECTIVE 4000 LEVEL
3 hours credit

Computer Science (CS) Courses

CS-1210 - INTRODUCTION TO COMPUTER PROGR
3 hours credit
CS-1410 - INTRODUCTION TO COMPUTER PROGRAMMING FOR SCIENTISTS This course is an introduction to computer programming for non-computer science majors. Topics include problem-solving, algorithm design, data types, control structures, repetition, loops, nested structures, modular programming and arrays. Three lecture hours and 1.5 hours of laboratory session per week. NOTE: Credit will be allowed for only one of CS 1410 or Engineering 1320. As well, CS 1410 may not be taken concurrently with, or after, CS 1510. Prerequisite: Grade XII academic mathematics
PREREQUISITE: Computer Science 1410L (concurrent with taking this course)
3 hours credit
CS-1410L - Computer Science 1410 Lab
PREREQUISITE: Computer Science 1410 (concurrent with taking this course)
CS-1520L - Computer Science 1520 Programming Workshop
PREREQUISITE: Computer Science 1520 (concurrent with taking this course)
CS-1610 - DIGITAL SYSTEMS This course provides an introduction to digital systems, beginning with elementary components such as logic gates, from which are constructed components such as adders and comparators, and progressing to more complex systems such as programmable logic devices, memory and processor units. Students acquire skills in the design and analysis of combinational and sequential digital systems, CAD design and simulation tools for complex systems, and construction of digital systems based upon a modular methodology. Three lecture hours and a three-hour laboratory session per week
PREREQUISITE: Computer Science 1610L (concurrent with taking this course)
3 hours credit
CS-1610L - Computer Science 1610 Lab
PREREQUISITE: Computer Science 1610 (concurrent with taking this course)
CS-1910 - COMPUTER SCIENCE I This course is an introduction to computer programming and is designed for both Computer Science majors and non-majors. Emphasis is on problem solving and software development using a modern high level object-oriented language. Topics include: the programming process; language syntax and semantics; data types; expressions; input and output; conditionals; loops; arrays; functions/methods and text files. The course follos an "objects late" strategy, deferring in-depth discussions of object-orientated concepts to Computer Science 192. Prerequisite: Grade XII academic mathematics.
PREREQUISITE: Computer Science 1910L (concurrent with taking this course)
3 hours credit
CS-1910L - Computer Science 1910 Lab
PREREQUISITE: Computer Science 1910 (concurrent with taking this course)
CS-1920 - COMPUTER SCEINCE II This course continues the development of object-oriented programming. Topics include class design; inheritance; interfaces and polymorphism; collection classes; searching and sorting; recursion; exception handling; the Model-View-Controller pattern; and graphical user interfaces.
PREREQUISITE: Computer Science 1920L; (concurrent with taking this course)
3 hours credit
CS-1920L - Computer Sceince 1920 Lab
PREREQUISITE: Computer Sceince 1920; (concurrent with taking this course)
CS-2060 - WEB DEVELOPMENT AND PROGRAMMING In this course, students learn to create websites that involve server-side scripting and database operations. While one specific scripting language is used to acquire web development and programming skills, students are exposed to a spectrum of scripting languages, enabling them to easily adapt to others. Three hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2120 - MOBILE DEVICE DEVELOPMENT - iOS This course introduces the student to programming for mobile devices that use iOS. The course will present a study of the architecture, operating system, and programming for these devices. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2130 - MOBILE DEVICE DEVELOPMENT - ANDROID This course introduces the student to programming for mobile devices that use the Android platform. The course will present a study of the architecture, operating system and programming language of these devices. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or CS-1920 (prior to taking this course)
3 hours credit
CS-2520 - COMPUTER ORGANIZATION AND ARCHITECTURE This course provides a basic understanding of the organization and architecture of modern computer systems. It examines the function and design of major hardware components both from a designer's perspective and through assembly language programming. Topics include components and their interconnection, internal/external memory, input/output subsystems, processors, computer arithmetic, instruction sets, addressing modes, and pipelining. Three hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 (prior to taking this course)
3 hours credit
CS-2610 - DATA STRUCTURES AND ALGORITHMS This course continues the study of data structures, recursive algorithms, searching and sorting techniques, and general strategies for problem solving. It also introduces complexity analysis and complexity classes. Three lecture hours per week
PREREQUISITE: Computer Science 1520 and six credit hours of Mathematics (prior to taking this course)
3 hours credit
CS-2620 - COMPARATIVE PROGRAMMING LANGUAGES This course examines the principal features of major types of programming languages, including procedural, logical, functional and object-oriented languages. Features include parameter-passing mechanisms, control structures, scope, and binding rules. Each language type is illustrated by considering a specific language. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-2710 - PRACTICAL EMBEDDED SYSTEMS This course introduces students to the concept of embedded systems architectures, the interconnection of sensors and actuators to such systems, and the usage of such platforms for data acquisition and control of automated systems. Popular microcontroller units and system-on-chip platforms will be examined. Three lecture hours per week
PREREQUISITE: Computer Science 1210 or Computer Science 1410 or Computer Science 1510 or Engineering 1310 or CS-1920 (prior to taking this course)
3 hours credit
CS-2820 - PROGRAMMING PRACTICES This course introduces the student to development in the Unix/Linux environment. Topics include development tools, shell programming, common utility programs, processes, file/directory management, IDEs, testing/debugging, version control, and an introduction to software engineering. Three lecture hours per week
PREREQUISITE: Computer Science 1520 or Computer Science 1920 permission of the instructor (based on completion of CS 1510 with first class standing) (prior to taking this course)
3 hours credit
CS-2910 - COMPUTER SCIENCE III This is the third course in the Computer Science programming sequence. It covers more advanced programming concepts in an object oriented language. It also serves as an introduction to data structures and software engineering. Topics included: the programming toolchain; threads; class generics; lists, stacks, queues and binary trees; streams and binary I/O, object serialization, networking (sockets and web interface); introduction to software engineering; relational database connectivity; and XML parsing.
PREREQUISITE: Computer Science 1920 and 6 Math credits (prior to taking this course)
3 hours credit
CS-2910L - Computer Science 2910 Lab
PREREQUISITE: Computer Science 2910; (concurrent with taking this course)
CS-2920 - DATA STRUCTURES AND ALGORITHMS This course continues the study of data structures, recursive algorithms, searching and sorting techniques, and general strategies for problem solving. It also introduces complexity analysis and complexity classes. Three lecture hours per week
PREREQUISITE: Computer Science 2910 and 6 Math credits (prior to taking this course)
3 hours credit
CS-2920L - Computer Science 2920 Lab
PREREQUISITE: Computer Science 2920; (concurrent with taking this course)
CS-3110 - VIDEO GAME DESIGN This course focuses on the process from initial idea to final design of a video game. Students will craft a game document from an original concept of their own creation and create a prototype of the game based on that document. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3210 - HUMAN-COMPUTER INTERFACE DESIGN This course is an introduction to the design and evaluation of software interfaces and webpages. The course focuses on user-centered design and includes topics such as user analysis and modelling, iterative prototyping, usability testing, designing for the web, internationalization and localization. Three hours per week
PREREQUISITE: Computer Science 1520 (prior to taking this course)
3 hours credit
CS-3220 - INTRODUCTION TO BIOINFORMATICS This course is an introduction to bioinformatics, with a focus on a practical guide to the analysis of data on genes and proteins. It familiarizes students with the tools and principles of contemporary bioinformatics. Students acquire a working knowledge of a variety of publicly available data and computational tools important in bioinformatics, and a grasp of the underlying principles enabling them to evaluate and use novel techniques as they arise in the future. Cross-listed with Biology, Pathology/Microbiology, Human Biology (cf. Biology 3220, VPM 8850, HB 8850). Three lecture hours and a one-hour laboratory session per week. NOTE: No student can be awarded more than one course credit among HB 8850, VPM 8850, CS 3220 and BIO 3220.
PREREQUISITE: Computer Science 3220L (concurrent with taking this course)
3 hours credit
CS-3220L - Computer Science 3220 Lab
PREREQUISITE: Computer Science 3220 (concurrent with taking this course)
CS-3320 - THEORY OF COMPUTING
3 hours credit
CS-3420 - COMPUTER COMMUNICATIONS This course introduces the basic principles of modern computer communication: protocols, architectures and standards. Topics include layered architectures, data transmission, error and flow control, medium access, routing, congestion control and common internet application protocols. Three lecture hours per week
PREREQUISITE: Computer Science 2520 and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-3520 - OPERATING SYSTEMS This course introduces the student to the major concepts of modern operating systems. Topics covered include: process management, memory management, file systems, device management and security. Three lecture hours per week
PREREQUISITE: Computer Science 2520, Computer Science 2610, and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-3610 - ANALYSIS AND DESIGN OF ALGORITHMS This course, which introduces the study of algorithm design and measures of efficiency, is a continuation of CS 2610. Topics include algorithm complexity and analysis; techniques such as divide and conquer, greedy and dynamic programming; searching and sorting algorithms; graph algorithms; text processing; efficient algorithms for several common computer science problems and NP-completeness. Three lecture hours per week
PREREQUISITE: Computer Science 2610 and Math 2420 (prior to taking this course)
3 hours credit
CS-3620 - SOFTWARE DESIGN AND ARCHITECTURE This course examines the principles and best practices in object-oriented (OO) software design. Topics include a review of foundational OO concepts, OO design principles, classic design patterns, and software architectures. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3710 - DATABASE SYSTEMS This course introduces the fundamental concepts necessary for the design, use and implementation of database systems. Topics discussed include logical and physical organization of data, database models, design theory, data definition and manipulation languages, constraints, views, and embedding database languages in general programming languages. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-3840 - TECHNOLOGY MANAGEMENT & ENTREPRENEURSHIP This course provides an overview on how to start and sustain a technology-oriented company. Topics discussed will include the role of technology in society, intellectual property, patents, business plans, financial planning, sources of capital, business structure, liability, tax implications, sales, marketing, operational and human resource management. This course will be taught using problem-based and experiential learning strategies with involvement from real life entrepreneurs as motivators and facilitators. (Cross-listed with Engineering 4430. Three lecture hours per week.
PREREQUISITE: Computer Science 2520, Computer Science 2620, and Computer Science 2820 (prior to taking this course)
3 hours credit
CS-4060 - CLOUD COMPUTING This course examines: the critical technology trends that are enabling cloud computing, the architecture and the design of existing deployments, the services and the applications they offer, and the challenges that need to be addressed to help cloud computing to reach its full potential. The format of this course will be a mix of lectures, seminar-style discussions, and student presentations. Three lecture hours per week
PREREQUISITE: Computer Science 2060 (prior to taking this course)
3 hours credit
CS-4110 - ARTIFICIAL INTELLIGENCE AND AUTOMATED REASONING This course introduces general problem-solving methods associated with automated reasoning and simulated intelligence. Topics include problem abstraction, state space heuristic search theory, pathfinding, flocking behaviour, knowledge representation, propositional logic, reasoning with uncertainty, machine learning and connectionism. Three lecture hours per week
PREREQUISITE: Computer Science 2610 (prior to taking this course)
3 hours credit
CS-4120 - MACHINE LEARNING AND DATA MINING Machine learning is the study of mechanisms for acquiring knowledge from large data sets. This course examines techniques for detecting patterns in sets of uncategorized data. Supervised and unsupervised learning techniques are studied, with particular application to real-world data. Three lecture hours per week
PREREQUISITE: Computer Science 3710 and Statistics 2210 (prior to taking this course)
3 hours credit
CS-4230 - PHYSICS OF GAMING
3 hours credit
CS-4350 - COMPUTER GRAPHICS PROGRAMMING This course introduces the student to the principles and tools of applied graphics programming including graphical systems, input and interaction, object modeling, transformations, hidden surface removal, and shading and lighting models. Languages, graphics libraries and toolkits, and video game engines are introduced, as well as relevant graphics standards. Three lecture hours per week
PREREQUISITE: Computer Science 2620 and Math 2610 (prior to taking this course)
3 hours credit
CS-4360 - ADVANCED COMPUTER GRAPHICS PROGRAMMING This course builds on the computer graphics programming concepts introduced in CS 4350. Students are given a deeper understanding of the components of the 3D graphics pipeline, and how they are used in modern graphical applications. Topics include advanced texture mapping, practical uses of vertex and pixel shaders, screen post-processing, particle systems, and graphics engine design. Three lecture hours per week
PREREQUISITE: Computer Science 4350 (prior to taking this course)
3 hours credit
CS-4440 - DATA SCIENCE Data science is an interdisciplinary and emerging field where techniques from several areas are used to solve problems using data. This course provides an overview and hands-on training in data science, where students will learn to combine tools and techniques from computer science, statistics, data visualization and the social sciences. The course will focus on: 1) the process of moving from data collection to product, 2) tools for preparing, manipulating and analyzing data sets (big and small), 3) statistical modelling and machine learning, and 4) real world challenges. Three lecture hours per week
PREREQUISITE: Computer Science 3710 and Statistics 2210 (prior to taking this course)
3 hours credit
CS-4610 - WIRELESS SENSOR NETWORKS This course is an introduction to Wireless Sensor Networks. It includes the following topics: single-node architecture, wireless sensor network architecture, physical layer, MAC protocols, link-layer protocols, naming and addressing, time synchronization, localization and positioning, topology control, routing protocols, transport layer, and quality of service. Three lecture hours per week
PREREQUISITE: Computer Science 2520 and Computer Science 2610 (prior to taking this course)
3 hours credit
CS-4650 - VIDEO-GAME ARCHITECTURE This programming-driven course aims to explore the various systems that comprise a typical video-game project, including event systems, state machines, rendering, scripting and AI programming. Students will implement these components throughout the course with the end goal of building a small game. Three lectures hours per week
PREREQUISITE: Computer Science 4360
3 hours credit
CS-4720 - COMPILER DESIGN This is a first course in compiler design. The course covers: compilation phases, lexical analysis, parsing, scope rules, block structure, symbol tables, run-time heap and stack management, code generation, pre-processing, compiler-compilers, and translation systems. Three lecture hours per week
PREREQUISITE: MCS 3320 (prior to taking this course)
3 hours credit
CS-4810 - SOFTWARE ENGINEERING This course emphasizes the theory, methods and tools employed in developing medium to large-scale software which is usable, efficient, maintainable, and dependable. Project management is a major focus. Topics include traditional and agile process models, project costing, scheduling, team organization and management, requirements modelling/specification, software design, software verification and testing, and re-engineering. Three lecture hours per week. Restriction: Student must have fourth year standing in Computer Science
3 hours credit
CS-4820 - SOFTWARE SYSTEMS DEVELOPMENT PROJECT In this course, students propose, complete and present a significant software project in a group setting using the system development skills learned in CS 4810. The course applies object-oriented design principles through the use of UML. Students are encouraged to select (with the consent of the instructor) a project with a real-world client. One lecture hour per week plus significant project time
PREREQUISITE: Computer Science 4810 (May be taken concurrently in exceptional circumstances) (prior to taking this course)
3 hours credit
CS-4830 - VIDEO GAME PROGRAMMING PROJECT In this course, students work as a group to develop a single design into a fully functioning video game. This course applies the project management skills learned in CS 4810 to the development of a professional quality video game based upon a single design and prototype emerging from CS 3110. One lecture hour per week plus significant project time. Semester hours of credit: 6
PREREQUISITE: Computer Science 3110, Computer Science 4810 and enrolment in the Computer Science with Video Game Programming major. (prior to taking this course)
6 hours credit
CS-4840 - PROTOTYPE SYSTEMS DEVELOPMENT This course is for student teams who wish to develop an early prototype of a product which they hope to pitch to an external start-up accelerator program post-graduation. Student teams may be inter-disciplinary, but students must register for this course (or its equivalent) within their home school/department. Entry into the course is dependent upon a pitch for the product being judged as economically viable by a team of project mentors. Pitches are made at the conclusion of CS 3840. One lecture hour per week plus significant project time. Semester hours of credit: 6
PREREQUISITE: Computer Science 3840 and permission of the instructor (prior to taking this course)
6 hours credit
CS-ELEC - COMPUTER SCIENCE ELECTIVE
3 hours credit
CS-ELEC1 - COMP. SCI. ELECTIVE 1000 LEVEL
3 hours credit
CS-ELEC2 - COMP. SCI. ELECTIVE 2000 LEVEL
3 hours credit
CS-ELEC3 - COMP SCI ELECTIVE
3 hours credit
CS-ELEC4 - COMP SCI ELECTIVE 4000 LEVEL
3 hours credit

Applied Mathematical Sciences (AMS) Courses

AMS-2160 - MATHEMATICS OF FINANCE This first course in the mathematics of finance includes topics such as measurement of interest; annuities and perpetuities; amortization and sinking funds; rates of return; bonds and related securities; life insurance. Three lecture hours a week
PREREQUISITE: Math 1910 (prior to taking this course)
3 hours credit
AMS-2160L - Mathematics of Finance Lab
PREREQUISITE: AMS 2160 (concurrent with taking this course)
AMS-2400 - FINANCIAL MATHEMATICS & INVESTMENTS Advanced topics of Theory of Interest as initially covered in AMS 2160 including time value of money, annuities, loans, bonds, general cash flows, portfolios and immunization concepts, as well as an introduction to capital markets, analysis of equity and fixed income investments, and an introduction to derivative securities including futures, forwards, swaps and options. Three lecture hours plus a two hour lab per week
PREREQUISITE: AMS 2400L (concurrent with taking this course)
3 hours credit
AMS-2400L - Financial Mathematics and Investments Lab
PREREQUISITE: AMS 2400 (concurrent with taking this course)
AMS-2400T - AMS 2400 TUTORIAL
PREREQUISITE: AMS-2400; (concurrent with taking this course)
AMS-2410 - FINANCIAL ECONOMICS I Introduction to mathematical techniques used to price and hedge derivative securities in modern finance. Modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes. Applications of derivatives in practice will also be discussed. Three lecture hours a week
PREREQUISITE: AMS 2410 Lab (concurrent with taking this course)
3 hours credit
AMS-2410L - Financial Economics Lab I
PREREQUISITE: AMS 2410 (concurrent with taking this course)
AMS-2510 - ACTUARIAL SCIENCE I This course will explore the future lifetime random variable, probability and survival functions, force of mortality; complete and curtate expectation of life, and Makeham and Gompertz mortality laws. Other topics will include: Life tables, characteristics of population and insurance life tables, selection, and fractional age assumptions. Life insurance payments and annuity payments: Present value random variables; expected present values; higher moments; actuarial notation, annual, 1/mthly and continuous cases, relationships between insurance and annuity functions. Premiums, expense loadings, present value of future loss random variables and distribution, net and gross cases, the equivalence principle and portfolio percentile principle will also be discussed. Three lecture hours a week
PREREQUISITE: AMS-2510L (concurrent with taking this course)
3 hours credit
AMS-2510L - Actuarial Science Lab 1
PREREQUISITE: AMS 2510 (concurrent with taking this course)
AMS-2860 - ACTUARIAL MATHEMATICS LAB I This lab features problem-solving sessions for the professional examination on financial mathematics of the Society of Actuaries and the Casualty Actuarial Society. Semester hours of credit: 1
PREREQUISITE: AMS 2160 (prior to taking this course)
3 hours credit
AMS-2940 - OPTIMIZATION An introduction to the methods and applications of linear programming. Topics include linear programming formulations, the simplex method, duality and sensitivity analysis, and integer programming basics. Applications to transportation, resource allocation and scheduling problems will be examined. Software will be used to illustrate topics and applications. Three lecture hours per week
PREREQUISITE: MATH 2610 (prior to taking this course)
3 hours credit
AMS-3160 - GAME THEORY The course covers the fundamentals of game theory and its applications to the modeling of competition and cooperation in business, economics, biology and society. It will include two-person games in strategic form and Nash equilibria, extensive form games, including multi-stage games, coalition games and the core Bayesian games, mechanism design and auctions. PREREQUISITES: Math 192, Math 242 and Stat 222 Three lecture hours per week
PREREQUISITE: Math 1920, Math 2420 and Statistics 2220 (prior to taking this course)
3 hours credit
AMS-3310 - ADVANCED CORPORATE FINANCE FOR ACTUARIES This course covers various advanced topics in corporate finance, with emphasis on theories of corporate incentives and asymmetric information. Illustrative applications using cases are provided. Topics include: capital budgeting, real options, investment decision using Markowitz and utility theory, the Capital Asset Pricing Model, Arbitrage Pricing Theory, market efficiency and capital structure and dividend policy. Other topics may include time value of money, capital budgeting, cost of capital, security issuance, capital structure, payout policy and dividends, short-term finance, and risk management. Where suitable, topics are treated from a mathematical and quantitative perspective. Three lecture hours per week
PREREQUISITE: AMS 2400 and BUS 2310 (prior to taking this course)
3 hours credit
AMS-3410 - FINANCIAL ECONOMICS II This course will discuss advanced mathematical techniques used to price and hedge derivative securities in modern finance. Topics include: modelling, analysis and computations for financial derivative products, including exotic options and swaps in all asset classes. Students will also have the opportunity to apply these derivatives in practice. Three lecture hours per week
PREREQUISITE: AMS 3410L (concurrent with taking this course)
3 hours credit
AMS-3410L - Financial Economics II Lab
PREREQUISITE: AMS 3410 (concurrent with taking this course)
AMS-3510 - ACTUARIAL SCIENCE II This course will discuss: policy values, annual, 1/mthly and continuous cases, Thiele's equation, policy alterations, modified policies and multiple state models. Other topics will include applications in life contingencies, assumptions, Kolmogorov equations, premiums, policy values, multiple decrement models, Joint Life Models, Valuation of insurance benefits on joint lives, and dependent and independent cases. Three lecture hours per week
PREREQUISITE: AMS-3510L (concurrent with taking this course)
3 hours credit
AMS-3510L - Actuarial Science II Lab
PREREQUISITE: AMS 3510 (concurrent with taking this course)
AMS-3730 - ADVANCED INSURANCE AND ACTUARIAL PRACTICES This course is a study of cash flow projection methods for pricing, reserving and profit testing. Topics include: deterministic, stochastic and stress testing; pricing and risk management of embedded options in insurance products; mortality and maturity guarantees for equity-linked life insurance. Three lecture hours per week
PREREQUISITE: AMS 3510 (prior to taking this course)
3 hours credit
AMS-3770 - COMBINATORIAL OPTIMIZATION In this course, various algorithms will be considered, including minimum spanning tree, shortest path, maximum flow, and maximum matching. The links with linear and integer programming will also be considered, with particular attention to duality. Three lecture hours per week
PREREQUISITE: MATH 2420 and AMS 2940 (prior to taking this course)
3 hours credit
AMS-3910 - MATHEMATICAL MODELLING This course studies the process of mathematical modeling, namely, formulating a "real-world" problem in mathematical terms, solving the resulting mathematical problem, and interpreting the solution. Major topics include the modeling of optimization problems (using the techniques of linear programming), and deterministic and probabilistic dynamical processes (with models formulated as differential and difference equations). Applications are taken from science, business and other areas, according to class interest. Three lecture hours per week
PREREQUISITE: A statistics course (prior to taking this course)
3 hours credit
AMS-4080 - FINANCIAL MATHEMATICS II This course explores calculus in a stochastic environment. Topics include: random functions, derivative, chain rule, integral, integration by parts, partial derivatives, pricing forwards and options. Ito's lemma and financial applications, Hull-White, Artzner-Heath, and Brennan-Schwartz models Martingales, pricing methodology, and risk-neutral probability will also be discussed. Three lecture hours per week
PREREQUISITE: MATH 2610 and AMS 3410 (prior to taking this course)
3 hours credit
AMS-4090 - FINANCIAL MATHEMATICS III This course discusses forming risk-free portfolios, the Black-Scholes partial differential equation, constant dividend case, exotic options, drift adjustment, and equivalent martingale measures. Topics also include: Cox-Ross-Rubinstein, Merton and Vasicek's models, stochastic optimization, Hamilton-Jacobi-Bellman equation, and application to American options. Three lecture hours per week
PREREQUISITE: AMS 4080 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4540 - LOSS MODELS I This course explores models for loss severity, parametric models, effect of policy modifications, and tail behaviour. Topics also include: models for loss frequency: (a, b, 0), (a, b, 1), mixed Poisson models; compound Poisson models, Aggregate claims models: moments and moment generating function: recursion and Classical ruin theory. Three lecture hours per week
PREREQUISITE: AMS 3510 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4550 - LOSS MODELS II This course is a study of the mathematics of survival models and includes some examples of parametric survival models. Topics include: tabular survival models, estimates from complete and incomplete data samples, parametric survival models, and determining the optimal parameters. Maximum likelihood estimators, derivation and properties, product limit estimators, Kaplan-Meier and Nelson-Aalen, credibility theory: limited fluctuation; Bayesian; Buhlmann; Buhlmann-Straub; empirical Bayes parameter estimation; statistical inference for loss models; maximum likelihood estimation; the effect of policy modifications; and model selection will also be discussed. Three lecture hours per week
PREREQUISITE: AMS 4540 (prior to taking this course)
3 hours credit
AMS-4580 - CREDIBILITY THEORY This course is a credibility approach to inference for heterogeneous data; classical, regression and Bayesian models; with illustrations from insurance data. Three lecture hours per week
PREREQUISITE: AMS 3510 and STAT 3220 (prior to taking this course)
3 hours credit
AMS-4680 - NONLINEAR OPTIMIZATION This course is a study of unconstrained optimization, optimality conditions (necessary, sufficient and Karush-Kuhn-Tucker), penalty functions, convex functions, and convex programming. Three lecture hours per week
PREREQUISITE: MATH 2910 and AMS 2940 (prior to taking this course)
3 hours credit
AMS-4780 - QUANTITATIVE RISK MANAGEMENT This course is an introduction to financial risk management. Topics include: risk measures, modeling for multivariate distributions and copulas, market, credit and operational risk. Advanced topics in quantitative risk management will also be discussed. Three lecture hours per week
PREREQUISITE: AMS 3310 (prior to taking this course)
3 hours credit
AMS-ELEC1 - APP. MATH ELECTIVE 1000 LEVEL
3 hours credit
AMS-ELEC2 - APP. MATH ELECTIVE 2000 LEVEL
3 hours credit
AMS-ELEC3 - APP. MATH ELECTIVE 3000 LEVEL
3 hours credit
AMS-ELEC4 - APP. MATH ELECTIVE 4000 LEVEL
3 hours credit

Mathematical and Computational Sciences (MCS) Courses

MCS-2010 - MAPLE TECHNOLOGY LAB An introduction to the software package MAPLE. Topics include the basic functions and commands, mathematical problem solving using MAPLE, and programming in the internal MAPLE language. Two lab hours per week for 6 weeks. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Math 1920 (prior to taking this course)
1 hour credit
MCS-2020 - MATLAB TECHNOLOGY LAB An introduction to the software package Matlab. Topics include the basic functions and commands, programming and problem-solving using Matlab. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Math 2610 (prior to taking this course)
1 hour credit
MCS-2030 - R TECHNOLOGY LAB An introduction to the software package R. Topics include the basic functions and commands, programming and problem-solving using R. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and Statistics 2220 (prior to taking this course)
1 hour credit
MCS-2040 - VISUAL BASIC IN EXCEL TECHNOLOGY LAB An introduction to the software package Excel and Visual Basic in the Excel environment. Topics include the basic functions and commands, programming and problem-solving using Excel and Visual Basic. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and AMS 2400 (prior to taking this course)
1 hour credit
MCS-2050 - GGY AXIS TECHNOLOGY LAB An introduction to the software package GGY AXIS. Topics include the basic functions and commands, programming and problem-solving using GGY AXIS. Two lab hours per week for 6 weeks Semester hours of credit: 1
PREREQUISITE: Computer Science 1510 and AMS 2510 (prior to taking this course)
1 hour credit
MCS-2840 - CO-OP CAREER SKILLS I This course offers introductory career skills training to prepare co-op students for their first work term. Students are assessed on a pass/fail basis. Cross-listed with Business (cf. Business 2920) Semester hours of credit: 0 Restriction: Student must be admitted into the Mathematical and Computational Sciences Co-operative Education Program
MCS-2850 - CO-OP WORK TERM I This course is a co-op students' first work term. A work term report related to a technical problem/issue within the organization where the student is working is required. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 2840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-3050 - TUTORING IN MATHEMATICAL AND COMPUTATIONAL SCIENCES Students are introduced to techniques for facilitating learning in the Mathematical and Computational Sciences, and then put these techniques into practice by mediating student group learning either in introductory Mathematical and Computational Sciences courses, Mathematical and Computational Science Help Centre or in outreach programs to High Schools. Semester hours of credit: 1
PREREQUISITE: At least 36 credit hours completed in courses in the School of Mathematical and Computational Sciences (prior to taking this course)
1 hour credit
MCS-3320 - THEORY OF COMPUTING This course introduces automata theory, formal languages and computability. Topics include: finite automata; regular expressions; regular, context-free, and context-sensitive languages; computability models; algorithmic decidable and undecidable problems. Three lecture hours per week
PREREQUISITE: Computer Science 2610 and Math 2420 (prior to taking this course)
3 hours credit
MCS-3500 - QUANTUM INFORMATION Introduction to quantum information science; the field of studying, storing, processing and communicating information using quantum systems. Topic include quantum mechanics for Qubit Systems, foundations of Quantum Computing, algorithms, communication and cryptography. Three lecture hours per week.
PREREQUISITE: Math 2620 (prior to taking this course)
3 hours credit
MCS-3840 - CO-OP CAREER SKILLS II This course offers career skills training to strengthen co-op students' readiness for their second work term. Students are assessed on a pass/fail basis. Cross-listed with Business (cf. Business 3920) Semester hours of credit: 0
PREREQUISITE: MCS 2850 (prior to taking this course)
MCS-3850 - CO-OP WORK TERM II This course is a co-op students' second work term. Students will submit a report summarizing their work term achievements. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 3840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-3920 - NUMERICAL ANALYSIS Approximate solution of equations, various interpolative or iterative methods, especially Newton's; convergence tests and rates of convergence; roundoff and truncation errors; propagation of error in calculations; interpolating polynomials; Gauss-Jordan and other methods for simultaneous linear equations; inversion of matrices; determinants and eigenvalues; simultaneous nonlinear equations; evaluation of definite integrals; approximate derivatives; initial-value ordinary differential equations; least-squares curve fitting. Three lecture hours per week
PREREQUISITE: Math 3010 and Computer Science 1510 or equivalent (prior to taking this course)
3 hours credit
MCS-3950 - This course provides students with an opportunity to pursue special topics in Mathematical and Computational Science. Content varies from year to year. Three lecture hours per week. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-4210 - PROFESSIONAL COMMUNICATION AND PRACTICE This course aims to build students' oral and written communications skills, and to prepare them for a professional environment. Using examples from their discipline, students will focus on such aspects as description of processes, presentation of data, extended abstracts, correct use of terminology, and sensitivity to language and tone. Discussions of topics relevant to the professional Mathematical and Computational Scientist are also a key part of the course. Three hours per week
PREREQUISITE: At least 36 credit hours completed in the School of Mathematical and Computational Sciences (prior to taking this course)
3 hours credit
MCS-4420 - CRYPTOGRAPHY AND CODES This course is a study of classic and modern methods of encryption, applications to public-key ciphers, random number generators, attacks on encryption systems, error correcting codes; and computational number theory. Three lecture hours per week
PREREQUISITE: Math 3420 (prior to taking this course)
3 hours credit
MCS-4840 - CO-OP CAREER SKILLS III This course offers career skills training to strengthen co-op students' readiness for their third work term. Students are assessed on a pass/fail basis. Cross-listed with Business 4920 and Physics 4840 Semester hours of credit: 0
PREREQUISITE: MCS 3850 (prior to taking this course)
MCS-4850 - CO-OP WORK TERM III This course is a co-op students' third work term. Students will submit a report summarizing their work term achievements. Students are assessed on a pass/fail basis. Three semester hours of credit
PREREQUISITE: MCS 4840 or permission of the Academic Director of Co-operative Education. (prior to taking this course)
3 hours credit
MCS-4860 - CO-OP WORK TERM IV This optional work term is only available to co-op students in the School of Mathematical and Computational Sciences, who elect for a fourth work term. The goal is to add further value for the student, integrating classroom theory with professional skills acquired during the work term. Semester hours of credit: 0
PREREQUISITE: MCS 4850 (prior to taking this course)
MCS-4900 - HONOURS PROJECT This course is intended to give research experience to students planning to pursue graduate studies in an area of Mathematical and Computational Sciences, or planning a career where research experience would be an asset. It provides students with the opportunity to do an independent research project on Mathematical or Computational Sciences topic, under the supervision of a faculty member. Some or all of the work may be done during the summer months. Semester hours of credit: 6 Restriction: Student must be accepted to an Honours program in the School of Mathematical and Computational Sciences
6 hours credit
MCS-4910 - DIRECTED STUDIES IN MATHEMATICAL AND COMPUTATIONAL SCIENCES These courses are designed and recommended for students in the Mathematical and Computational Sciences to encourage independent initiative and study. Reading and research will be conducted in one or more specialized areas. (See Academic Regulation 9 for Regulations Governing Directed Studies.) Three semester hours of credit. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-4950 - ADVANCED TOPICS IN MATHEMATICAL AND COMPUTATIONAL SCIENCES This course provides students with an opportunity to pursue advanced topics in Mathematical and Computational Sciences. Content varies from year to year but is always at a fourth-year level. Prospective students should contact the School of Mathematical and Computational Sciences for a more detailed description of any particular year's offering. Three lecture hours per week. Restriction: Student must have permission of the instructor.
3 hours credit
MCS-ELEC1 - MCS ELECTIVE 1000 LEVEL
3 hours credit
MCS-ELEC2 - MCS ELECTIVE 2000 LEVEL
3 hours credit
MCS-ELEC3 - MCS ELECTIVE 3000 LEVEL
3 hours credit
MCS-ELEC4 - MCS ELECTIVE 4000 LEVEL
3 hours credit

Information Technology (IT) Courses

IT-1210 - INTRODUCTION TO COM PROGRAM
3 hours credit
IT-1320 - This course will address traditional storytelling and the challenges of interactive narrative. Students will develop a solid understanding of traditional narrative theory as well as experimental approaches to storytelling in literature, theatre and film with relevance to game development. Three lecture hours per week
3 hours credit
IT-3710 - This course is an introduction to relational database concepts and design for non-computer science majors. Topics include the logical and physical organization of data, database models, design theory, data definition and manipulation languages, constraints, views, database security, data warehousing and data mining.
3 hours credit
IT-ELEC1 - INFO TECH ELECTIVE 1000 LEVEL
3 hours credit
IT-ELEC2 - INFO TECH ELECTIVE 2000 LEVEL
3 hours credit
IT-ELEC3 - INFO TECH ELECTIVE 3000 LEVEL
3 hours credit
IT-ELEC4 - INFO TECH ELECTIVE 4000 LEVEL
3 hours credit

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Courses for all degrees, majors, minors, and co-operative study in the School of Mathematical and Computational Sciences can be found in the "Courses" tab.

Calendar Courses

Courses for all degrees, majors, minors, and co-operative study in the School of Mathematical and Computational Sciences can be found in the "Courses" tab.

Calendar Courses

SMCS Courses

Courses for all degrees, majors, minors, and co-operative study in the School of Mathematical and Computational Sciences can be found in the "Courses" tab.

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