³ÉÈËVRÊÓƵ

Major Computer Science - Computer Games (67 credits)

important

Note: This is the 2018–2019 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .

Offered by: Computer Science     Degree: Bachelor of Science

Program Requirements

This program is a specialization within Computer Science. It fulfils all the basic requirements of the Major Computer Science. Complementary courses focus on topics that are important to understanding the technology behind computer games and to gaining experience in software development and design needed for computer game development.

Students may complete this program with a minimum of 62 credits or a maximum of 67 credits depending if they are exempt from taking COMP 202 and their choice of complementary courses.

Required Courses (50 credits)

* Students who have sufficient knowledge in a programming language do not need to take COMP 202 and can replace it with additional computer science complementary course credits.

  • COMP 202 Foundations of Programming (3 credits) *

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Introduction to computer programming in a high level language: variables, expressions, primitive types, methods, conditionals, loops. Introduction to algorithms, data structures (arrays, strings), modular software design, libraries, file input/output, debugging, exception handling. Selected topics.

    Terms: Fall 2018, Winter 2019, Summer 2019

    Instructors: Alberini, Giulia; Vybihal, Joseph P (Fall) Alberini, Giulia; Yu, Tzu-Yang; Zammar, Chad (Winter) Yu, Tzu-Yang (Summer)

    • 3 hours

    • Prerequisite: a CEGEP level mathematics course

    • Restrictions: COMP 202 and COMP 208 cannot both be taken for credit. COMP 202 is intended as a general introductory course, while COMP 208 is intended for students interested in scientific computation. COMP 202 cannot be taken for credit with or after COMP 250

  • COMP 206 Introduction to Software Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Comprehensive overview of programming in C, use of system calls and libraries, debugging and testing of code; use of developmental tools like make, version control systems.

    Terms: Fall 2018, Winter 2019

    Instructors: Meger, David (Fall) Vybihal, Joseph P; Zammar, Chad (Winter)

  • COMP 250 Introduction to Computer Science (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Mathematical tools (binary numbers, induction, recurrence relations, asymptotic complexity, establishing correctness of programs), Data structures (arrays, stacks, queues, linked lists, trees, binary trees, binary search trees, heaps, hash tables), Recursive and non-recursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.

    Terms: Fall 2018, Winter 2019

    Instructors: Langer, Michael; Alberini, Giulia (Fall) Robillard, Martin; Alberini, Giulia (Winter)

    • 3 hours

    • Prerequisites: Familiarity with a high level programming language and CEGEP level Math.

    • Students with limited programming experience should take COMP 202 or equivalent before COMP 250. See COMP 202 Course Description for a list of topics.

  • COMP 251 Algorithms and Data Structures (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Introduction to algorithm design and analysis. Graph algorithms, greedy algorithms, data structures, dynamic programming, maximum flows.

    Terms: Fall 2018, Winter 2019

    Instructors: Waldispuhl, Jérôme (Fall) Devroye, Luc P; McLeish, Erin Leigh (Winter)

    • 3 hours

    • Prerequisite: COMP 250

    • Corequisite(s): MATH 235 or MATH 240 or MATH 363.

    • COMP 251 uses mathematical proof techniques that are taught in the corequisite course(s). If possible, students should take the corequisite course prior to COMP 251.

    • COMP 251 uses basic counting techniques (permutations and combinations) that are covered in MATH 240 and 363, but not in MATH 235. These techniques will be reviewed for the benefit of MATH 235 students.

    • Restrictions: Not open to students who have taken or are taking COMP 252.

  • COMP 273 Introduction to Computer Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Number representations, combinational and sequential digital circuits, MIPS instructions and architecture datapath and control, caches, virtual memory, interrupts and exceptions, pipelining.

    Terms: Fall 2018, Winter 2019

    Instructors: Kry, Paul (Fall) Siddiqi, Kaleem (Winter)

  • COMP 302 Programming Languages and Paradigms (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Programming language design issues and programming paradigms. Binding and scoping, parameter passing, lambda abstraction, data abstraction, type checking. Functional and logic programming.

    Terms: Fall 2018, Winter 2019

    Instructors: Pientka, Brigitte (Fall) Panangaden, Prakash (Winter)

  • COMP 303 Software Design (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Principles, mechanisms, techniques, and tools for object-oriented software design and its implementation, including encapsulation, design patterns, and unit testing.

    Terms: Fall 2018, Winter 2019

    Instructors: Nassif, Mathieu; Vybihal, Joseph P (Fall) Guo, Jin (Winter)

  • COMP 308 Computer Systems Lab (1 credit)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Digital circuitry and programming interface of peripheral circuit boards (cards), e.g., graphics cards; introduction to tools and libraries that interact with the card; performance issues.

    Terms: This course is not scheduled for the 2018-2019 academic year.

    Instructors: There are no professors associated with this course for the 2018-2019 academic year.

  • COMP 310 Operating Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Control and scheduling of large information processing systems. Operating system software - resource allocation, dispatching, processors, access methods, job control languages, main storage management. Batch processing, multiprogramming, multiprocessing, time sharing.

    Terms: Fall 2018, Winter 2019

    Instructors: Maheswaran, Muthucumaru (Fall) Vybihal, Joseph P (Winter)

  • COMP 322 Introduction to C++ (1 credit)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Basics and advanced features of the C++ language. Syntax, memory management, class structure, method and operator overloading, multiple inheritance, access control, stream I/O, templates, exception handling.

    Terms: Winter 2019

    Instructors: Zammar, Chad (Winter)

  • COMP 330 Theory of Computation (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Finite automata, regular languages, context-free languages, push-down automata, models of computation, computability theory, undecidability, reduction techniques.

    Terms: Fall 2018

    Instructors: Panangaden, Prakash (Fall)

  • COMP 361D1 Software Engineering Project (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Software development process in practice: requirement elicitation and analysis, software design, implementation, integration, test planning, and maintenance. Application of the core concepts and techniques through the realization of a large software system.

    Terms: Fall 2018

    Instructors: Kienzle, Jorg Andreas (Fall)

  • COMP 361D2 Software Engineering Project (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : See COMP 361D1 for course description.

    Terms: Winter 2019

    Instructors: Kienzle, Jorg Andreas (Winter)

    • Prerequisite: COMP 361D1

    • No credit will be given for this course unless both COMP 361D1 and COMP 361D2 are successfully completed in consecutive terms

  • COMP 557 Fundamentals of Computer Graphics (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Fundamental mathematical, algorithmic and representational issues in computer graphics: overview of graphics pipeline, homogeneous coordinates, projective transformations, line-drawing and rasterization, hidden surface removal, surface modelling (quadrics, bicubics, meshes), rendering (lighting, reflectance models, ray tracing, texture mapping), compositing colour perception, and other selected topics.

    Terms: Fall 2018

    Instructors: Kry, Paul (Fall)

  • MATH 222 Calculus 3 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Taylor series, Taylor's theorem in one and several variables. Review of vector geometry. Partial differentiation, directional derivative. Extreme of functions of 2 or 3 variables. Parametric curves and arc length. Polar and spherical coordinates. Multiple integrals.

    Terms: Fall 2018, Winter 2019, Summer 2019

    Instructors: Macdonald, Jeremy; Faifman, Dmitry (Fall) Sektnan, Lars (Winter) Pequignot, Yann Batiste (Summer)

  • MATH 223 Linear Algebra (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Review of matrix algebra, determinants and systems of linear equations. Vector spaces, linear operators and their matrix representations, orthogonality. Eigenvalues and eigenvectors, diagonalization of Hermitian matrices. Applications.

    Terms: Fall 2018, Winter 2019

    Instructors: Kelome, Djivede (Fall) Macdonald, Jeremy (Winter)

    • Fall and Winter

    • Prerequisite: MATH 133 or equivalent

    • Restriction: Not open to students in Mathematics programs nor to students who have taken or are taking MATH 236, MATH 247 or MATH 251. It is open to students in Faculty Programs

  • MATH 240 Discrete Structures 1 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Mathematical foundations of logical thinking and reasoning. Mathematical language and proof techniques. Quantifiers. Induction. Elementary number theory. Modular arithmetic. Recurrence relations and asymptotics. Combinatorial enumeration. Functions and relations. Partially ordered sets and lattices. Introduction to graphs, digraphs and rooted trees.

    Terms: Fall 2018, Winter 2019

    Instructors: Macdonald, Jeremy; Nica, Bogdan (Fall) Macdonald, Jeremy; Pequignot, Yann Batiste (Winter)

    • Fall and Winter

    • Corequisite: MATH 133.

    • Restriction: For students in any Computer Science, Computer Engineering, or Software Engineering programs. Others only with the instructor's permission. Not open to students who have taken or are taking MATH 235.

  • MATH 323 Probability (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Sample space, events, conditional probability, independence of events, Bayes' Theorem. Basic combinatorial probability, random variables, discrete and continuous univariate and multivariate distributions. Independence of random variables. Inequalities, weak law of large numbers, central limit theorem.

    Terms: Fall 2018, Winter 2019, Summer 2019

    Instructors: Stephens, David (Fall) Wolfson, David B (Winter) Kelome, Djivede (Summer)

    • Prerequisites: MATH 141 or equivalent.

    • Restriction: Intended for students in Science, Engineering and related disciplines, who have had differential and integral calculus

    • Restriction: Not open to students who have taken or are taking MATH 356

Complementary Courses (17 credits)

Students complete a minimum of 15 or a maximum of 17 complementary credits selected as follows:

3 credits selected from:

  • COMP 350 Numerical Computing (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Computer representation of numbers, IEEE Standard for Floating Point Representation, computer arithmetic and rounding errors. Numerical stability. Matrix computations and software systems. Polynomial interpolation. Least-squares approximation. Iterative methods for solving a nonlinear equation. Discretization methods for integration and differential equations.

    Terms: Fall 2018

    Instructors: Chang, Xiao-Wen (Fall)

  • COMP 360 Algorithm Design (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Advanced algorithm design and analysis. Linear programming, complexity and NP-completeness, advanced algorithmic techniques.

    Terms: Fall 2018, Winter 2019

    Instructors: Reed, Bruce Alan (Fall) Reed, Bruce Alan (Winter)

6-8 credits selected from:

  • COMP 424 Artificial Intelligence (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Introduction to search methods. Knowledge representation using logic and probability. Planning and decision making under uncertainty. Introduction to machine learning.

    Terms: Winter 2019

    Instructors: Cheung, Jackie (Winter)

  • COMP 521 Modern Computer Games (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Genre and history of games, basic game design, storytelling and narrative analysis, game engines, design of virtual worlds, real-time 2D graphics, game physics and physical simulation, pathfinding and game AI, content generation, 3D game concerns, multiplayer and distributed games, social issues.

    Terms: Fall 2018

    Instructors: Verbrugge, Clark (Fall)

  • COMP 522 Modelling and Simulation (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Simulation and modelling processes, state automata, Petri Nets, state charts, discrete event systems, continuous-time models, hybrid models, system dynamics and object-oriented modelling.

    Terms: This course is not scheduled for the 2018-2019 academic year.

    Instructors: There are no professors associated with this course for the 2018-2019 academic year.

  • COMP 529 Software Architecture (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Development, analysis, and maintenance of software architectures, with special focus on modular decomposition and reverse engineering.

    Terms: Winter 2019

    Instructors: Robillard, Martin (Winter)

  • COMP 533 Model-Driven Software Development (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Model-driven software development; requirements engineering based on use cases and scenarios; object-oriented modelling using UML and OCL to establish complete and precise analysis and design documents; mapping to Java. Introduction to meta-modelling and model transformations, use of modelling tools.

    Terms: Fall 2018

    Instructors: Kienzle, Jorg Andreas (Fall)

  • COMP 551 Applied Machine Learning (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.

    Terms: Fall 2018, Winter 2019

    Instructors: Chandar, Sarath (Fall) Hamilton, William (Winter)

    • Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent

    • Restriction(s): Not open to students who have taken COMP 598 when topic was "Applied Machine Learning"

    • Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.

  • COMP 559 Fundamentals of Computer Animation (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Fundamental mathematical and computational issues in computer animation with a focus on physics based simulation: overview of numerical integration methods, accuracy and absolute stability, stiff systems and constraints, rigid body motion, collision detection and response, friction, deformation, stable fluid simulation, use of motion capture, and other selected topics.

    Terms: Winter 2019

    Instructors: Kry, Paul (Winter)

6 credits selected from:

  • COMP 409 Concurrent Programming (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Characteristics and utility of concurrent programs; formal methods for specification, verification and development of concurrent programs; communications, synchronization, resource allocation and management, coherency and integrity.

    Terms: Winter 2019

    Instructors: Verbrugge, Clark (Winter)

  • COMP 421 Database Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Database Design: conceptual design of databases (e.g., entity-relationship model), relational data model, functional dependencies. Database Manipulation: relational algebra, SQL, database application programming, triggers, access control. Database Implementation: transactions, concurrency control, recovery, query execution and query optimization.

    Terms: Winter 2019

    Instructors: D'silva, Joseph (Winter)

  • COMP 535 Computer Networks 1 (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Fundamental design principles, elements, and protocols of computer networks, focusing on the current Internet. Topics include: layered architecture, direct link networks, switching and forwarding, bridge routing, congestion control, end-to-end protocols application of DNS, HTTP, P2P, fair queuing, performance modeling and analysis.

    Terms: Winter 2019

    Instructors: Naboulsi, Diala (Winter)

Faculty of Science—2018-2019 (last updated Aug. 22, 2018) (disclaimer)
Back to top