Program Requirements
Students may complete this program with a minimum of 72 credits or a maximum of 75 credits depending if they are exempt from taking COMP 202.
Honours students must maintain a CGPA of at least 3.00 during their studies and at graduation.
Required Courses (48 credits)
* Students who have sufficient knowledge in a programming language do not need to take COMP 202.
** Students take either MATH 340 or MATH 350.

COMP 202 Foundations of Programming (3 credits) *
Overview
Computer Science (Sci) : Introduction to programming in a modern highlevel language, modular software design and debugging. Programming concepts are illustrated using a variety of application areas.
Terms: Fall 2015, Winter 2016, Summer 2016
Instructors: Melanie LymanAbramovitch, Daniel Pomerantz (Fall) Yang Cai, Jackie Cheung, Melanie LymanAbramovitch (Winter) Daniel Pomerantz (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)
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 2015, Winter 2016
Instructors: David Meger, Gregory L Dudek (Fall) Joseph P Vybihal (Winter)

COMP 250 Introduction to Computer Science (3 credits)
Overview
Computer Science (Sci) : An introduction to the design of computer algorithms, including basic data structures, analysis of algorithms, and establishing correctness of programs. Overview of topics in computer science.
Terms: Fall 2015, Winter 2016
Instructors: Mathieu Blanchette, Jérôme Waldispuhl (Fall) Claude Crepeau (Winter)

COMP 252 Honours Algorithms and Data Structures (3 credits)
Overview
Computer Science (Sci) : The design and analysis of data structures and algorithms. The description of various computational problems and the algorithms that can be used to solve them, along with their associated data structures. Proving the correctness of algorithms and determining their computational complexity.
Terms: Winter 2016
Instructors: Luc P Devroye (Winter)
3 hours
Restrictions: Open only to students registered in following programs: Honours in Computer Science, Joint Honours in Mathematics and Computer Science, Honours in Applied Mathematics, Honours in Mathematics. Not open to students who have taken or are taking COMP 251.
Note: COMP 252 can be used instead of COMP 251 to satisfy prerequisites.

COMP 273 Introduction to Computer Systems (3 credits)
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 2015, Winter 2016
Instructors: Paul Kry (Fall) Michael Langer (Winter)
3 hours
Corequisite: COMP 206.

COMP 302 Programming Languages and Paradigms (3 credits)
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 2015, Winter 2016
Instructors: Brigitte Pientka (Fall) Prakash Panangaden (Winter)
3 hours
Prerequisite: COMP 250

COMP 303 Software Development (3 credits)
Overview
Computer Science (Sci) : Principles, mechanisms, techniques, and tools for objectoriented software development: encapsulation, design patterns, unit testing, etc.
Terms: Fall 2015, Winter 2016
Instructors: Joseph P Vybihal (Fall) Martin Robillard (Winter)

COMP 310 Operating Systems (3 credits)
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 2015, Winter 2016
Instructors: Muthucumaru Maheswaran (Fall) Muthucumaru Maheswaran (Winter)
3 hours
Prerequisite: COMP 273
 COMP 330 Theory of Computation (3 credits)

COMP 350 Numerical Computing (3 credits)
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. Leastsquares approximation. Iterative methods for solving a nonlinear equation. Discretization methods for integration and differential equations.
Terms: Fall 2015
Instructors: XiaoWen Chang (Fall)

COMP 362 Honours Algorithm Design (3 credits)
Overview
Computer Science (Sci) : Basic algorithmic techniques, their applications and limitations. Problem complexity, how to deal with problems for which no efficient solutions are known.
Terms: Winter 2016
Instructors: Bruce Alan Reed (Winter)

COMP 400 Project in Computer Science (3 credits)
Overview
Computer Science (Sci) : A computer related project, typically a programming effort, along with a report will be carried out in cooperation with a staff member in the School of Computer Science.
Terms: Fall 2015, Winter 2016, Summer 2016
Instructors: Nathan Friedman (Fall) Nathan Friedman (Winter) Nathan Friedman (Summer)
3 hours
Prerequisites: 15 Computer Science credits.
Restriction: For Honours students

MATH 222 Calculus 3 (3 credits)
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 2015, Winter 2016, Summer 2016
Instructors: Stephen W Drury, Jingyin Huang (Fall) Stephen W Drury (Winter) Geoffrey McGregor (Summer)

MATH 223 Linear Algebra (3 credits)
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 2015, Winter 2016
Instructors: Thomas F Fox (Fall) Michael Pichot (Winter)

MATH 240 Discrete Structures 1 (3 credits)
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 2015
Instructors: Adrian Roshan Vetta (Fall)

MATH 340 Discrete Structures 2 (3 credits) **
Overview
Mathematics & Statistics (Sci) : Review of mathematical writing, proof techniques, graph theory and counting. Mathematical logic. Graph connectivity, planar graphs and colouring. Probability and graphs. Introductory group theory, isomorphisms and automorphisms of graphs. Enumeration and listing.
Terms: Winter 2016
Instructors: Sergey Norin (Winter)

MATH 350 Graph Theory and Combinatorics (3 credits) **
Overview
Mathematics & Statistics (Sci) : Graph models. Graph connectivity, planarity and colouring. Extremal graph theory. Matroids. Enumerative combinatorics and listing.
Terms: Fall 2015
Instructors: Sergey Norin (Fall)
Complementary Courses (27 credits)
6 credits selected from:

MATH 318 Mathematical Logic (3 credits)
Overview
Mathematics & Statistics (Sci) : Propositional calculus, truthtables, switching circuits, natural deduction, first order predicate calculus, axiomatic theories, set theory.
Terms: Fall 2015
Instructors: Marcin Sabok (Fall)
Fall
Restriction: Not open to students who are taking or have taken PHIL 210

MATH 323 Probability (3 credits)
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 2015, Winter 2016, Summer 2016
Instructors: William J Anderson (Fall) Irene Vrbik (Winter) Djivede Kelome (Summer)

MATH 324 Statistics (3 credits)
Overview
Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Terms: Fall 2015, Winter 2016
Instructors: Johanna Neslehova (Fall) Christian Genest (Winter)
Fall and Winter
Prerequisite: MATH 323 or equivalent
Restriction: Not open to students who have taken or are taking MATH 357
You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.
The remaining credits selected from computer science courses at the 300 level or above (except COMP 364 and COMP 396) and ECSE 539. At least 12 credits must be at the 500 level.