Statistics and Computer Science
This program provides students with a solid training in both computer science and statistics together with the necessary mathematical background. As statistical endeavours involve ever increasing amounts of data, some students may want training in both disciplines. The Honours program is a challenging program providing students with a solid training in both computer science and statistics suitable for entry into graduate school in either discipline.
DETAILED PROGRAM OUTLINES:
Program Requirement:
This program provides students with a solid training in both computer science and statistics together with the necessary mathematical background. As statistical endeavours involve ever increasing amounts of data, some students may want training in both disciplines.
Program Prerequisites
Students entering the Joint Major in Statistics and Computer Science are normally expected to have completed the courses below or their equivalents. Otherwise they will be required to make up any deficiencies in these courses over and above the 72 credits of required courses.

MATH 133 Linear Algebra and Geometry 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Systems of linear equations, matrices, inverses, determinants; geometric vectors in three dimensions, dot product, cross product, lines and planes; introduction to vector spaces, linear dependence and independence, bases. Linear transformations. Eigenvalues and diagonalization.
Offered by: Mathematics and Statistics
 3 hours lecture, 1 hour tutorial
 Prerequisite: a course in functions
 Restriction A: Not open to students who have taken MATH 221 or CEGEP objective 00UQ or equivalent.
 Restriction B: Not open to students who have taken or are taking MATH 123, except by permission of the Department of Mathematics and Statistics.
 Restriction C: Not open to students who are taking or have taken MATH 134.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Rosalie BélangerRioux, Piotr Przytycki
 Djivede A Kelome

MATH 140 Calculus 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Review of functions and graphs. Limits, continuity, derivative. Differentiation of elementary functions. Antidifferentiation. Applications.
Offered by: Mathematics and Statistics
 3 hours lecture, 1 hour tutorial
 Prerequisite: High School Calculus
 Restriction: Not open to students who have taken MATH 120, MATH 139 or CEGEP objective 00UN or equivalent
 Restriction: Not open to students who have taken or are taking MATH 122, except by permission of the Department of Mathematics and Statistics
 Each Tutorial section is enrolment limited
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Jérôme Fortier

MATH 141 Calculus 2 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): The definite integral. Techniques of integration. Applications. Introduction to sequences and series.
Offered by: Mathematics and Statistics
 Prerequisites: MATH 139 or MATH 140 or MATH 150.
 Restriction: Not open to students who have taken MATH 121 or CEGEP objective 00UP or equivalent
 Restriction Note B: Not open to students who have taken or are taking MATH 122, except by permission of the Department of Mathematics and Statistics.
 Each Tutorial section is enrolment limited
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Jérôme Fortier, Marcin Sabok
 Sidney Trudeau
Required Courses (51 credits)
* Students who have sufficient knowledge in a programming language do not need to take COMP 202 but can replace it with an additional Computer Science complementary course.
** Students take either COMP 350 or MATH 317, but not both.
*** Students take either MATH 223 or MATH 236, but not both.
Both courses are equivalent as prerequisites for required and complementary Computer Science courses listed below.

COMP 202 Foundations of Programming 3 Credits*
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 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
 Symbols:
 *
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Giulia Alberini, Jonathan C Campbell
 Giulia Alberini

COMP 206 Intro to Software Systems 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Joseph V D'silva
 Joseph V D'silva

COMP 250 Intro to Computer Science 3 Credits
 Fall
 Winter
 Summer
Offered in the: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 nonrecursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.
Offered by: Computer Science
 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.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Giulia Alberini
 Giulia Alberini

COMP 251 Algorithms and Data Structures 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Introduction to algorithm design and analysis. Graph algorithms, greedy algorithms, data structures, dynamic programming, maximum flows.
Offered by: Computer Science
 3 hours
 Prerequisite: COMP 250
 Corequisite(s): MATH 235 or MATH 240.
 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 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.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Jérôme Waldispuhl, David C Becerra
 David C Becerra

COMP 273 Intro to Computer Systems 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Number representations, combinational and sequential digital circuits, MIPS instructions and architecture datapath and control, caches, virtual memory, interrupts and exceptions, pipelining.
Offered by: Computer Science
 3 hours
 Corequisite: COMP 206.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Kaleem Siddiqi
 Paul Kry, HsiuChin Lin

COMP 302 Programming Lang & Paradigms 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Brigitte Pientka

COMP 330 Theory of Computation 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Finite automata, regular languages, contextfree languages, pushdown automata, models of computation, computability theory, undecidability, reduction techniques.
Offered by: Computer Science
 3 hours
 Prerequisite: COMP 251.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Hamed Hatami
 Prakash Panangaden

COMP 350 Numerical Computing 3 Credits**
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 3 hours
 Prerequisites: MATH 222 and MATH 223 and one of: COMP 202, COMP 208, COMP 250; or equivalents.
 Restrictions: Students cannot receive credit for both COMP 350 and MATH 317.
 Symbols:
 **
 Terms
 Fall 2020
 Instructors
 XiaoWen Chang

COMP 360 Algorithm Design 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Advanced algorithm design and analysis. Linear programming, complexity and NPcompleteness, advanced algorithmic techniques.
Offered by: Computer Science
 3 hours
 Prerequisite: Either COMP 251 or COMP 252, and either MATH 240 or MATH 235 or MATH 363.
 Restriction: Not open to students who have taken or are taking COMP 362.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Bruce Alan Reed

MATH 222 Calculus 3 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Mathematics and Statistics
 Prerequisite: MATH 141. Familiarity with vector geometry or Corequisite: MATH 133
 Restriction: Not open to students who have taken CEGEP course 201303 or MATH 150, MATH 151 or MATH 227
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Djivede A Kelome, Jérôme Fortier
 Jerome Vetois

MATH 223 Linear Algebra 3 Credits***
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Mathematics and Statistics
 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
 Symbols:
 ***
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Michael Y Pichot

MATH 235 Algebra 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Sets, functions and relations. Methods of proof. Complex numbers. Divisibility theory for integers and modular arithmetic. Divisibility theory for polynomials. Rings, ideals and quotient rings. Fields and construction of fields from polynomial rings. Groups, subgroups and cosets; group actions on sets.
Offered by: Mathematics and Statistics
 Fall
 3 hours lecture; 1 hour tutorial
 Prerequisite: MATH 133 or equivalent
 Symbols:
 Terms
 Fall 2020
 Instructors
 Daniel T Wise

MATH 236 Algebra 2 3 Credits***
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Linear equations over a field. Introduction to vector spaces. Linear mappings. Matrix representation of linear mappings. Determinants. Eigenvectors and eigenvalues. Diagonalizable operators. CayleyHamilton theorem. Bilinear and quadratic forms. Inner product spaces, orthogonal diagonalization of symmetric matrices. Canonical forms.
Offered by: Mathematics and Statistics
 Winter
 Prerequisite: MATH 235
 Symbols:
 ***
 Terms
 Winter 2021
 Instructors
 There are no professors associated with this course for the 20202021 academic year

MATH 242 Analysis 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): A rigorous presentation of sequences and of real numbers and basic properties of continuous and differentiable functions on the real line.
Offered by: Mathematics and Statistics
 Fall
 Prerequisite: MATH 141
 Restriction(s): Not open to students who are taking or who have taken MATH 254.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Axel W Hundemer

MATH 314 Advanced Calculus 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Derivative as a matrix. Chain rule. Implicit functions. Constrained maxima and minima. Jacobians. Multiple integration. Line and surface integrals. Theorems of Green, Stokes and Gauss. Fourier series with applications.
Offered by: Mathematics and Statistics
 Prerequisites: MATH 133, MATH 222
 Restriction: Not open to students who have taken or are taking MATH 248 or MATH 358.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Charles Roth
 John A Toth

MATH 317 Numerical Analysis 3 Credits**
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Error analysis. Numerical solutions of equations by iteration. Interpolation. Numerical differentiation and integration. Introduction to numerical solutions of differential equations.
Offered by: Mathematics and Statistics
 Fall
 Prerequisites: MATH 315 or MATH 325 or MATH 263, and COMP 202 or permission of instructor.
 Restrictions: Not open to students who have taken COMP 350
 Symbols:
 **
 Terms
 Fall 2020
 Instructors
 Peter Bartello

MATH 323 Probability 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Mathematics and Statistics
 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
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 David B Wolfson, Alia Sajjad
 David B Wolfson, Alia Sajjad

MATH 324 Statistics 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Offered by: Mathematics and Statistics
 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.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Masoud AsgharianDastenaei
 Yi Yang

MATH 423 Applied Regression 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Multiple regression estimators and their properties. Hypothesis tests and confidence intervals. Analysis of variance. Prediction and prediction intervals. Model diagnostics. Model selection. Introduction to weighted least squares. Basic contingency table analysis. Introduction to logistic and Poisson regression. Applications to experimental and observational data.
Offered by: Mathematics and Statistics
 Fall
 Prerequisites: MATH 324, and MATH 223 or MATH 236
 Restriction: Not open to students who have taken or are taking MGSC 372.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Yi Yang
12 credits in Mathematics selected from:
* Students take either MATH 340 or MATH 350, but not both.
** MATH 578 and COMP 540 cannot both be taken for program credit.

MATH 208 Intro to Statistical Computing 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Basic data management. Data visualization. Exploratory data analysis and descriptive statictics. Writing functions. Simulation and parallel computing. Communication data and documenting code for reproducible research.
Offered by: Mathematics and Statistics
 Prerequisite(s): MATH 133
 Symbols:
 Terms
 Fall 2020
 Instructors
 Russell Steele

MATH 308 Fundls of Statistical Learning 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Theory and application of various techniques for the exploration and analysis of multivariate data: principal component analysis, correspondence analysis, and other visualization and dimensionality reduction techniques; supervised and unsupervised learning; linear discriminant analysis, and clustering techniques. Data applications using appropriate software.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Christian Genest

MATH 327 Matrix Numerical Analysis 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): An overview of numerical methods for linear algebra applications and their analysis. Problem classes include linear systems, least squares problems and eigenvalue problems.
Offered by: Mathematics and Statistics
 Winter
 Prerequisites: MATH 223 or MATH 236 or MATH 247 or MATH 251, COMP 202 or consent of instructor.
 Symbols:
 Terms
 Winter 2021
 Instructors
 Adam M Oberman

MATH 340 Discrete Mathematics 3 Credits*
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Discrete Mathematics and applications. Graph Theory: matchings, planarity, and colouring. Discrete probability. Combinatorics: enumeration, combinatorial techniques and proofs.
Offered by: Mathematics and Statistics
 Winter
 Prerequisites: MATH 235 or MATH 240 or MATH 242.
 Corequisites: MATH 223 or MATH 236.
 Restriction: Restriction: Not open to students who have taken or are taking MATH 350.
 Symbols:
 *
 Terms
 Winter 2021
 Instructors
 Jérôme Fortier

MATH 350 Honours Discrete Mathematics 3 Credits*
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Discrete mathematics. Graph Theory: matching theory, connectivity, planarity, and colouring; graph minors and extremal graph theory. Combinatorics: combinatorial methods, enumerative and algebraic combinatorics, discrete probability.
Offered by: Mathematics and Statistics
 Prerequisites: MATH 235 or MATH 240 and MATH 251 or MATH 223.
 Restrictions: Not open to students who have taken or are taking MATH 340. Intended for students in mathematics or computer science honours programs.
 Intended for students in mathematics or computer science honours programs.
 Symbols:
 *
 Terms
 Fall 2020
 Instructors
 Sergey Norin

MATH 352 Problem Seminar 1 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Seminar in Mathematical Problem Solving. The problems considered will be of the type that occur in the Putnam competition and in other similar mathematical competitions.
Offered by: Mathematics and Statistics
 Prerequisite: Enrolment in a math related program or permission of the instructor. Requires departmental approval.
 Prerequisite: Enrolment in a math related program or permission of the instructor.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Sergey Norin

MATH 410 Majors Project 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): A supervised project.
Offered by: Mathematics and Statistics
 Prerequisite: Students must have 21 completed credits of the required mathematics courses in their program, including all required 200 level mathematics courses.
 Requires departmental approval.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Djivede A Kelome

MATH 427 Statistical Quality Control 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Introduction to quality management; variability and productivity. Quality measurement: capability analysis, gauge capability studies. Process control: control charts for variables and attributes. Process improvement: factorial designs, fractional replications, response surface methodology, Taguchi methods. Acceptance sampling: operating characteristic curves; single, multiple and sequential acceptance sampling plans for variables and attributes.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

MATH 447 Intro. to Stochastic Processes 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Conditional probability and conditional expectation, generating functions. Branching processes and random walk. Markov chains, transition matrices, classification of states, ergodic theorem, examples. Birth and death processes, queueing theory.
Offered by: Mathematics and Statistics
 Winter
 Prerequisite: MATH 323
 Restriction: Not open to students who have taken or are taking MATH 547.
 Symbols:
 Terms
 Winter 2021
 Instructors
 Elliot Paquette

MATH 523 Generalized Linear Models 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, loglinear models. Multinomial models. Overdispersion and Quasilikelihood. Applications to experimental and observational data.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Johanna Neslehova

MATH 524 Nonparametric Statistics 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Distribution free procedures for 2sample problem: Wilcoxon rank sum, SiegelTukey, Smirnov tests. Shift model: power and estimation. Single sample procedures: Sign, Wilcoxon signed rank tests. Nonparametric ANOVA: KruskalWallis, Friedman tests. Association: Spearman's rank correlation, Kendall's tau. Goodness of fit: Pearson's chisquare, likelihood ratio, KolmogorovSmirnov tests. Statistical software packages used.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Fall 2020
 Instructors
 David B Wolfson

MATH 525 Sampling Theory & Applications 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Simple random sampling, domains, ratio and regression estimators, superpopulation models, stratified sampling, optimal stratification, cluster sampling, sampling with unequal probabilities, multistage sampling, complex surveys, nonresponse.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Russell Steele

MATH 545 Intro to Time Series Analysis 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Stationary processes; estimation and forecasting of ARMA models; nonstationary and seasonal models; statespace models; financial time series models; multivariate time series models; introduction to spectral analysis; long memory models.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

MATH 578 Numerical Analysis 1 4 Credits**
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Development, analysis and effective use of numerical methods to solve problems arising in applications. Topics include direct and iterative methods for the solution of linear equations (including preconditioning), eigenvalue problems, interpolation, approximation, quadrature, solution of nonlinear systems.
Offered by: Mathematics and Statistics
 Symbols:
 **
 Terms
 Fall 2020
 Instructors
 Gantumur Tsogtgerel

MATH 594 Topics in Mathematics&Stats 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): This course covers a topic in mathematics and/or statistics.
Offered by: Mathematics and Statistics
 Prerequisites: At least 30 credits in required or complementary courses from the Honours Mathematics, Honours Applied Mathematics, or Honours Probability and Statistics programs. Additional prerequisites may be imposed by the Department of Mathematics and Statistics depending on the nature of the topic.
 Restrictions: Requires permission of the Department of Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Sergey Norin
9 credits in Computer Science selected as follows:
At least 6 credits selected from:

COMP 424 Artificial Intelligence 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Introduction to search methods. Knowledge representation using logic and probability. Planning and decision making under uncertainty. Introduction to machine learning.
Offered by: Computer Science
 Symbols:
 Terms
 Winter 2021
 Instructors
 Jackie Cheung

COMP 462 Computational Biology Methods 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Application of computer science techniques to problems arising in biology and medicine, techniques for modeling evolution, aligning molecular sequences, predicting structure of a molecule and other problems from computational biology.
Offered by: Computer Science
 3 hours
 Prerequisites: COMP 251, and MATH 323 or MATH 203 or BIOL 309
 Restriction: Not open to students who have taken COMP 562. Not open to students who are taking or have taken COMP 561.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Mathieu Blanchette

COMP 526 Probabilistic Reasoning and AI 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Belief networks, Utility theory, Markov Decision Processes and Learning Algorithms.
Offered by: Computer Science
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

COMP 540 Matrix Computations 4 Credits**
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Designing and programming reliable numerical algorithms. Stability of algorithms and condition of problems. Reliable and efficient algorithms for solution of equations, linear least squares problems, the singular value decomposition, the eigenproblem and related problems. Perturbation analysis of problems. Algorithms for structured matrices.
Offered by: Computer Science
 Symbols:
 **
 Terms
 Winter 2021
 Instructors
 XiaoWen Chang

COMP 547 Cryptography & Data Security 4 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): This course presents an indepth study of modern cryptography and data security. The basic information theoretic and computational properties of classical and modern cryptographic systems are presented, followed by a cryptanalytic examination of several important systems. We will study the applications of cryptography to the security of systems.
Offered by: Computer Science
 Symbols:
 Terms
 Fall 2020
 Instructors
 Claude Crepeau

COMP 551 Applied Machine Learning 4 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent
 Restriction(s): Not open to students who have taken or are taking COMP 451.
 Some background in Artificial Intelligence is recommended, e.g. COMP424 or ECSE526, but not required.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Mohsen Ravanbakhsh
 Reihaneh Rabbany

COMP 564 Adv Comput'l Bio Meth&Research 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Fundamental concepts and techniques in computational structural biology, system biology. Techniques include dynamic programming algorithms for RNA structure analysis, molecular dynamics and machine learning techniques for protein structure prediction, and graphical models for gene regulatory and proteinprotein interaction networks analysis. Practical sessions with stateoftheart software.
Offered by: Computer Science
 Symbols:
 Terms
 Winter 2021
 Instructors
 Jérôme Waldispuhl

COMP 566 Discrete Optimization 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Use of computer in solving problems in discrete optimization. Linear programming and extensions. Network simplex method. Applications of linear programming. Vertex enumeration. Geometry of linear programming. Implementation issues and robustness. Students will do a project on an application of their choice.
Offered by: Computer Science
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

COMP 567 Discrete Optimization 2 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Formulation, solution and applications of integer programs. Branch and bound, cutting plane, and column generation algorithms. Combinatorial optimization. Polyhedral methods. A large emphasis will be placed on modelling. Students will select and present a case study of an application of integer programming in an area of their choice.
Offered by: Computer Science
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year
Program Requirement:
This is a challenging program providing students with a solid training in both computer science and statistics suitable for entry into graduate school in either discipline.
Students may complete this program with a minimum of 76 credits or a maximum of 79 credits depending on whether or not they are exempt from taking COMP 202.
Program Prerequisites
Students entering the Joint Honours in Statistics and Computer Science are normally expected to have completed the courses below or their equivalents. Otherwise, they will be required to make up any deficiencies in these courses over and above the 7679 credits of courses in the program.

MATH 133 Linear Algebra and Geometry 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Systems of linear equations, matrices, inverses, determinants; geometric vectors in three dimensions, dot product, cross product, lines and planes; introduction to vector spaces, linear dependence and independence, bases. Linear transformations. Eigenvalues and diagonalization.
Offered by: Mathematics and Statistics
 3 hours lecture, 1 hour tutorial
 Prerequisite: a course in functions
 Restriction A: Not open to students who have taken MATH 221 or CEGEP objective 00UQ or equivalent.
 Restriction B: Not open to students who have taken or are taking MATH 123, except by permission of the Department of Mathematics and Statistics.
 Restriction C: Not open to students who are taking or have taken MATH 134.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Rosalie BélangerRioux, Piotr Przytycki
 Djivede A Kelome

MATH 140 Calculus 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Review of functions and graphs. Limits, continuity, derivative. Differentiation of elementary functions. Antidifferentiation. Applications.
Offered by: Mathematics and Statistics
 3 hours lecture, 1 hour tutorial
 Prerequisite: High School Calculus
 Restriction: Not open to students who have taken MATH 120, MATH 139 or CEGEP objective 00UN or equivalent
 Restriction: Not open to students who have taken or are taking MATH 122, except by permission of the Department of Mathematics and Statistics
 Each Tutorial section is enrolment limited
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Jérôme Fortier

MATH 141 Calculus 2 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): The definite integral. Techniques of integration. Applications. Introduction to sequences and series.
Offered by: Mathematics and Statistics
 Prerequisites: MATH 139 or MATH 140 or MATH 150.
 Restriction: Not open to students who have taken MATH 121 or CEGEP objective 00UP or equivalent
 Restriction Note B: Not open to students who have taken or are taking MATH 122, except by permission of the Department of Mathematics and Statistics.
 Each Tutorial section is enrolment limited
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Jérôme Fortier, Marcin Sabok
 Sidney Trudeau
Required Courses (46 credits)
* Students who have sufficient knowledge in a programming language are not required to take COMP 202.
** Students take either MATH 251 or MATH 247, but not both.

COMP 202 Foundations of Programming 3 Credits*
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 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
 Symbols:
 *
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Giulia Alberini, Jonathan C Campbell
 Giulia Alberini

COMP 206 Intro to Software Systems 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Joseph V D'silva
 Joseph V D'silva

COMP 250 Intro to Computer Science 3 Credits
 Fall
 Winter
 Summer
Offered in the: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 nonrecursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.
Offered by: Computer Science
 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.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Giulia Alberini
 Giulia Alberini

COMP 252 Honours Algorithms&Data Struct 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 3 hours
 Prerequisite: COMP 250 and either MATH 235 or MATH 240
 Restrictions: (1) Open only to students in Honours programs. (2) Students cannot receive credit for both COMP 251 and COMP 252.
 COMP 252 uses basic combinatorial counting methods that are covered in MATH 240 but not in MATH 235. Students who are unfamiliar with these methods should speak with the instructor for guidance.
 Symbols:
 Terms
 Winter 2021
 Instructors
 Claude Crepeau

COMP 273 Intro to Computer Systems 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Number representations, combinational and sequential digital circuits, MIPS instructions and architecture datapath and control, caches, virtual memory, interrupts and exceptions, pipelining.
Offered by: Computer Science
 3 hours
 Corequisite: COMP 206.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Kaleem Siddiqi
 Paul Kry, HsiuChin Lin

COMP 302 Programming Lang & Paradigms 3 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Brigitte Pientka

COMP 330 Theory of Computation 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Finite automata, regular languages, contextfree languages, pushdown automata, models of computation, computability theory, undecidability, reduction techniques.
Offered by: Computer Science
 3 hours
 Prerequisite: COMP 251.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Hamed Hatami
 Prakash Panangaden

COMP 362 Honours Algorithm Design 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Basic algorithmic techniques, their applications and limitations. Problem complexity, how to deal with problems for which no efficient solutions are known.
Offered by: Computer Science
 3 hours
 Prerequisite: COMP 252
 Restriction: Not open to students who have taken or are taking COMP 360.
 Note: COMP 362 can be used instead of COMP 360 to satisfy prerequisites.
 Symbols:
 Terms
 Winter 2021
 Instructors
 Bruce Alan Reed

MATH 235 Algebra 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Sets, functions and relations. Methods of proof. Complex numbers. Divisibility theory for integers and modular arithmetic. Divisibility theory for polynomials. Rings, ideals and quotient rings. Fields and construction of fields from polynomial rings. Groups, subgroups and cosets; group actions on sets.
Offered by: Mathematics and Statistics
 Fall
 3 hours lecture; 1 hour tutorial
 Prerequisite: MATH 133 or equivalent
 Symbols:
 Terms
 Fall 2020
 Instructors
 Daniel T Wise

MATH 247 Honours Applied Linear Algebra 3 Credits**
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Matrix algebra, determinants, systems of linear equations. Abstract vector spaces, inner product spaces, Fourier series. Linear transformations and their matrix representations. Eigenvalues and eigenvectors, diagonalizable and defective matrices, positive definite and semidefinite matrices. Quadratic and Hermitian forms, generalized eigenvalue problems, simultaneous reduction of quadratic forms. Applications.
Offered by: Mathematics and Statistics
 Winter
 Prerequisite: MATH 133 or equivalent.
 Restriction: Intended for Honours Physics and Engineering students
 Restriction: Not open to students who have taken or are taking MATH 236, MATH 223 or MATH 251
 Symbols:
 **
 Terms
 Winter 2021
 Instructors
 Tim Hoheisel

MATH 248 Honours Vector Calculus 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Partial derivatives and differentiation of functions in several variables; Jacobians; maxima and minima; implicit functions. Scalar and vector fields; orthogonal curvilinear coordinates. Multiple integrals; arc length, volume and surface area. Line and surface integrals; irrotational and solenoidal fields; Green's theorem; the divergence theorem. Stokes' theorem; and applications.
Offered by: Mathematics and Statistics
 Fall and Winter and Summer
 Prerequisites: MATH 133 and MATH 222 or consent of Department.
 Restriction: Intended for Honours Physics, Computer Science, Physiology and Engineering students.
 Restriction: Not open to students who have taken or are taking MATH 314 or MATH 358.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Pengfei Guan

MATH 251 Honours Algebra 2 3 Credits**
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Linear equations over a field. Introduction to vector spaces. Linear maps and their matrix representation. Determinants. Canonical forms. Duality. Bilinear and quadratic forms. Real and complex inner product spaces. Diagonalization of selfadjoint operators.
Offered by: Mathematics and Statistics
 Winter
 Prerequisites: MATH 235 or permission of the Department
 Restriction: Not open to students who are taking or have taken MATH 247
 Symbols:
 **
 Terms
 Winter 2021
 Instructors
 Michael Lipnowski

MATH 255 Honours Analysis 2 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Basic pointset topology, metric spaces: open and closed sets, normed and Banach spaces, HÃ¶lder and Minkowski inequalities, sequential compactness, HeineBorel, Banach Fixed Point theorem. Riemann(Stieltjes) integral, Fundamental Theorem of Calculus, Taylor's theorem. Uniform convergence. Infinite series, convergence tests, power series. Elementary functions.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Vojkan Jaksic

MATH 356 Honours Probability 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Sample space, probability axioms, combinatorial probability. Conditional probability, Bayes' Theorem. Distribution theory with special reference to the Binomial, Poisson, and Normal distributions. Expectations, moments, moment generating functions, univariate transformations. Random vectors, independence, correlation, multivariate transformations. Conditional distributions, conditional expectation.Modes of stochastic convergence, laws of large numbers, Central Limit Theorem.
Offered by: Mathematics and Statistics
 Fall
 Prerequisite(s): MATH 243 or MATH 255, and MATH 222 or permission of the Department.
 Restriction: Not open to students who have taken or are taking MATH 323
 Symbols:
 Terms
 Fall 2020
 Instructors
 Linan Chen

MATH 357 Honours Statistics 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Data analysis. Estimation and hypothesis testing. Power of tests. Likelihood ratio criterion. The chisquared goodness of fit test. Introduction to regression analysis and analysis of variance.
Offered by: Mathematics and Statistics
 Winter
 Prerequisite: MATH 356 or equivalent
 Restriction: Not open to students who have taken or are taking MATH 324
 Symbols:
 Terms
 Winter 2021
 Instructors
 Johanna Neslehova

MATH 533 Regression and ANOVA 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Multivariate normal and chisquared distributions; quadratic forms. Multiple linear regression estimators and their properties. General linear hypothesis tests. Prediction and confidence intervals. Asymptotic properties of least squares estimators. Weighted least squares. Variable selection and regularization. Selected advanced topics in regression. Applications to experimental and observational data.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Fall 2020
 Instructors
 Abbas Khalili Mahmoudabadi
18 credits in Mathematics selected as follows:
3 credits selected from:

MATH 242 Analysis 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): A rigorous presentation of sequences and of real numbers and basic properties of continuous and differentiable functions on the real line.
Offered by: Mathematics and Statistics
 Fall
 Prerequisite: MATH 141
 Restriction(s): Not open to students who are taking or who have taken MATH 254.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Axel W Hundemer

MATH 254 Honours Analysis 1 3 Credits*
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Properties of R. Cauchy and monotone sequences, Bolzano Weierstrass theorem. Limits, limsup, liminf of functions. Pointwise, uniform continuity: Intermediate Value theorem. Inverse and monotone functions. Differentiation: Mean Value theorem, L'Hospital's rule, Taylor's Theorem.
Offered by: Mathematics and Statistics
 Prerequisite(s): MATH 141
 Restriction(s): Not open to students who are taking or who have taken MATH 242.
 Symbols:
 *
 Terms
 Fall 2020
 Instructors
 Vojkan Jaksic
* It is strongly recommended that students take MATH 254.
3 credits selected from:

MATH 387 Honours Numerical Analysis 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Error analysis. Numerical solutions of equations by iteration. Interpolation. Numerical differentiation and integration. Introduction to numerical solutions of differential equations.
Offered by: Mathematics and Statistics
 Taught in alternate years
 Winter (even years)
 Prerequisites: MATH 325 or MATH 315, COMP 202 or permission of instructor.
 Corequisites: MATH 255 or MATH 243.
 Restriction: Intended primarily for Honours students.
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

MATH 397 Hons Matrix Numerical Analysis 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): The course consists of the lectures of MATH 327 plus additional work involving theoretical assignments and/or a project. The final examination for this course may be different from that of MATH 327.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Adam M Oberman
At least 8 credits selected from:

MATH 523 Generalized Linear Models 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, loglinear models. Multinomial models. Overdispersion and Quasilikelihood. Applications to experimental and observational data.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Johanna Neslehova

MATH 524 Nonparametric Statistics 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Distribution free procedures for 2sample problem: Wilcoxon rank sum, SiegelTukey, Smirnov tests. Shift model: power and estimation. Single sample procedures: Sign, Wilcoxon signed rank tests. Nonparametric ANOVA: KruskalWallis, Friedman tests. Association: Spearman's rank correlation, Kendall's tau. Goodness of fit: Pearson's chisquare, likelihood ratio, KolmogorovSmirnov tests. Statistical software packages used.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Fall 2020
 Instructors
 David B Wolfson

MATH 525 Sampling Theory & Applications 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Simple random sampling, domains, ratio and regression estimators, superpopulation models, stratified sampling, optimal stratification, cluster sampling, sampling with unequal probabilities, multistage sampling, complex surveys, nonresponse.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Russell Steele

MATH 556 Mathematical Statistics 1 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Distribution theory, stochastic models and multivariate transformations. Families of distributions including locationscale families, exponential families, convolution families, exponential dispersion models and hierarchical models. Concentration inequalities. Characteristic functions. Convergence in probability, almost surely, in Lp and in distribution. Laws of large numbers and Central Limit Theorem. Stochastic simulation.
Offered by: Mathematics and Statistics
 Fall
 Prerequisite: MATH 357 or equivalent
 Symbols:
 Terms
 Fall 2020
 Instructors
 Abbas Khalili Mahmoudabadi

MATH 557 Mathematical Statistics 2 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Sampling theory (including largesample theory). Likelihood functions and information matrices. Hypothesis testing, estimation theory. Regression and correlation theory.
Offered by: Mathematics and Statistics
 Winter
 Prerequisite: MATH 556
 Symbols:
 Terms
 Winter 2021
 Instructors
 Masoud AsgharianDastenaei
The remaining Mathematics credits selected from:
** MATH 578 and COMP 540 cannot both be taken for program credit.

MATH 350 Honours Discrete Mathematics 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Discrete mathematics. Graph Theory: matching theory, connectivity, planarity, and colouring; graph minors and extremal graph theory. Combinatorics: combinatorial methods, enumerative and algebraic combinatorics, discrete probability.
Offered by: Mathematics and Statistics
 Prerequisites: MATH 235 or MATH 240 and MATH 251 or MATH 223.
 Restrictions: Not open to students who have taken or are taking MATH 340. Intended for students in mathematics or computer science honours programs.
 Intended for students in mathematics or computer science honours programs.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Sergey Norin

MATH 352 Problem Seminar 1 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Seminar in Mathematical Problem Solving. The problems considered will be of the type that occur in the Putnam competition and in other similar mathematical competitions.
Offered by: Mathematics and Statistics
 Prerequisite: Enrolment in a math related program or permission of the instructor. Requires departmental approval.
 Prerequisite: Enrolment in a math related program or permission of the instructor.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Sergey Norin

MATH 454 Honours Analysis 3 3 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Review of pointset topology: topological space, dense sets, completeness, compactness, connectedness and pathconnectedness, separability. ArzelaAscoli, StoneWeierstrass, Baire category theorems. Measure theory: sigma algebras, Lebesgue measure and integration, L^1 functions. Fatou's lemma, monotone and dominated convergence theorem. Egorov, Lusin's theorems. FubiniTonelli theorem.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Fall 2020
 Instructors
 Jerome Vetois

MATH 545 Intro to Time Series Analysis 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Stationary processes; estimation and forecasting of ARMA models; nonstationary and seasonal models; statespace models; financial time series models; multivariate time series models; introduction to spectral analysis; long memory models.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

MATH 578 Numerical Analysis 1 4 Credits**
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Development, analysis and effective use of numerical methods to solve problems arising in applications. Topics include direct and iterative methods for the solution of linear equations (including preconditioning), eigenvalue problems, interpolation, approximation, quadrature, solution of nonlinear systems.
Offered by: Mathematics and Statistics
 Symbols:
 **
 Terms
 Fall 2020
 Instructors
 Gantumur Tsogtgerel

MATH 587 Advanced Probability Theory 1 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): Probability spaces. Random variables and their expectations. Convergence of random variables in Lp. Independence and conditional expectation. Introduction to Martingales. Limit theorems including Kolmogorov's Strong Law of Large Numbers.
Offered by: Mathematics and Statistics
 Symbols:
 Terms
 Fall 2020
 Instructors
 Linan Chen

MATH 594 Topics in Mathematics&Stats 4 Credits
 Fall
 Winter
 Summer
Offered in the:Mathematics & Statistics (Sci): This course covers a topic in mathematics and/or statistics.
Offered by: Mathematics and Statistics
 Prerequisites: At least 30 credits in required or complementary courses from the Honours Mathematics, Honours Applied Mathematics, or Honours Probability and Statistics programs. Additional prerequisites may be imposed by the Department of Mathematics and Statistics depending on the nature of the topic.
 Restrictions: Requires permission of the Department of Mathematics and Statistics
 Symbols:
 Terms
 Winter 2021
 Instructors
 Sergey Norin
At least 6 credits selected from:

COMP 424 Artificial Intelligence 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Introduction to search methods. Knowledge representation using logic and probability. Planning and decision making under uncertainty. Introduction to machine learning.
Offered by: Computer Science
 Symbols:
 Terms
 Winter 2021
 Instructors
 Jackie Cheung

COMP 462 Computational Biology Methods 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Application of computer science techniques to problems arising in biology and medicine, techniques for modeling evolution, aligning molecular sequences, predicting structure of a molecule and other problems from computational biology.
Offered by: Computer Science
 3 hours
 Prerequisites: COMP 251, and MATH 323 or MATH 203 or BIOL 309
 Restriction: Not open to students who have taken COMP 562. Not open to students who are taking or have taken COMP 561.
 Symbols:
 Terms
 Fall 2020
 Instructors
 Mathieu Blanchette

COMP 526 Probabilistic Reasoning and AI 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Belief networks, Utility theory, Markov Decision Processes and Learning Algorithms.
Offered by: Computer Science
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

COMP 540 Matrix Computations 4 Credits**
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Designing and programming reliable numerical algorithms. Stability of algorithms and condition of problems. Reliable and efficient algorithms for solution of equations, linear least squares problems, the singular value decomposition, the eigenproblem and related problems. Perturbation analysis of problems. Algorithms for structured matrices.
Offered by: Computer Science
 Symbols:
 **
 Terms
 Winter 2021
 Instructors
 XiaoWen Chang

COMP 547 Cryptography & Data Security 4 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): This course presents an indepth study of modern cryptography and data security. The basic information theoretic and computational properties of classical and modern cryptographic systems are presented, followed by a cryptanalytic examination of several important systems. We will study the applications of cryptography to the security of systems.
Offered by: Computer Science
 Symbols:
 Terms
 Fall 2020
 Instructors
 Claude Crepeau

COMP 551 Applied Machine Learning 4 Credits
 Fall
 Winter
 Summer
Offered in the: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.
Offered by: Computer Science
 Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent
 Restriction(s): Not open to students who have taken or are taking COMP 451.
 Some background in Artificial Intelligence is recommended, e.g. COMP424 or ECSE526, but not required.
 Symbols:
 Terms
 Fall 2020
 Winter 2021
 Instructors
 Mohsen Ravanbakhsh
 Reihaneh Rabbany

COMP 552 Combinatorial Optimization 4 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Algorithmic and structural approaches in combinatorial optimization with a focus upon theory and applications. Topics include: polyhedral methods, network optimization, the ellipsoid method, graph algorithms, matroid theory and submodular functions.
Offered by: Computer Science
 4 hours
 Prerequisite: Math 350 or COMP 362 (or equivalent).
 Restriction: This course is reserved for undergraduate honours students and graduate students. Not open to students who have taken or are taking MATH 552.
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

COMP 564 Adv Comput'l Bio Meth&Research 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Fundamental concepts and techniques in computational structural biology, system biology. Techniques include dynamic programming algorithms for RNA structure analysis, molecular dynamics and machine learning techniques for protein structure prediction, and graphical models for gene regulatory and proteinprotein interaction networks analysis. Practical sessions with stateoftheart software.
Offered by: Computer Science
 Symbols:
 Terms
 Winter 2021
 Instructors
 Jérôme Waldispuhl

COMP 566 Discrete Optimization 1 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Use of computer in solving problems in discrete optimization. Linear programming and extensions. Network simplex method. Applications of linear programming. Vertex enumeration. Geometry of linear programming. Implementation issues and robustness. Students will do a project on an application of their choice.
Offered by: Computer Science
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year

COMP 567 Discrete Optimization 2 3 Credits
 Fall
 Winter
 Summer
Offered in the:Computer Science (Sci): Formulation, solution and applications of integer programs. Branch and bound, cutting plane, and column generation algorithms. Combinatorial optimization. Polyhedral methods. A large emphasis will be placed on modelling. Students will select and present a case study of an application of integer programming in an area of their choice.
Offered by: Computer Science
 Symbols:
 Terms
 This course is not scheduled for the 20202021 academic year
 Instructors
 There are no professors associated with this course for the 20202021 academic year