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Honours Statistics and Computer Science (79 credits)

Offered by: Mathematics and Statistics     Degree: Bachelor of Science

Program Requirements

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 76-79 credits of courses in the program.

  • MATH 133 Linear Algebra and Geometry (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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; quadratic loci in two and three dimensions.

    Terms: Fall 2013, Winter 2014, Summer 2014

    Instructors: Miljan Brakocevic, Djivede Kelome, Michael Bailey, William J Anderson (Fall) Jessica Banks, Sidney Trudeau (Winter)

    • 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, MATH 130 or MATH 131, except by permission of the Department of Mathematics and Statistics.
    • Restriction C: Not open to students who are taking or have taken MATH 134.
  • MATH 140 Calculus 1 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Review of functions and graphs. Limits, continuity, derivative. Differentiation of elementary functions. Antidifferentiation. Applications.

    Terms: Fall 2013, Winter 2014, Summer 2014

    Instructors: Axel W Hundemer, Daniel Disegni (Fall) Stephen W Drury (Winter)

    • 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 or MATH 130 or MATH 131, except by permission of the Department of Mathematics and Statistics
    • Each Tutorial section is enrolment limited
  • MATH 141 Calculus 2 (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : The definite integral. Techniques of integration. Applications. Introduction to sequences and series.

    Terms: Fall 2013, Winter 2014, Summer 2014

    Instructors: Ihsan Topaloglu (Fall) Axel W Hundemer, Ronan Conlon, Michael Brandenbursky (Winter) Michael Brandenbursky (Summer)

    • 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 or MATH 130 or MATH 131, except by permission of the Department of Mathematics and Statistics.
    • Each Tutorial section is enrolment limited

Required Courses (49 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) *

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Introduction to programming in a modern high-level language, modular software design and debugging. Programming concepts are illustrated using a variety of application areas.

    Terms: Fall 2013, Winter 2014, Summer 2014

    Instructors: Daniel Pomerantz, Jonathan Tremblay (Fall) Bettina Kemme, Jonathan Tremblay (Winter)

    • 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 2013, Winter 2014

    Instructors: Joseph P Vybihal (Fall) Joseph P Vybihal (Winter)

    • 3 hours
    • Prerequisite: COMP 202 or COMP 250
  • COMP 250 Introduction to Computer Science (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2013, Winter 2014

    Instructors: Mathieu Blanchette (Fall) Doina Precup, Mathieu Blanchette (Winter)

    • 3 hours
    • Prerequisites: Familiarity with a high level programming language and CEGEP level Math.
    • Restrictions: COMP 203 and COMP 250 are considered to be equivalent from a prerequisite point of view, and cannot both be taken for credit.
  • COMP 252 Honours Algorithms and Data Structures (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2014

    Instructors: Luc P Devroye (Winter)

    • 3 hours
    • Prerequisite: COMP 250 and MATH 240
    • 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)

    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 2013, Winter 2014

    Instructors: Joseph P Vybihal (Fall) Paul Kry (Winter)

    • 3 hours
    • Corequisite: COMP 206.
  • 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 2013, Winter 2014

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

    • 3 hours
    • Prerequisite: COMP 250
  • COMP 330 Theory of Computation (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Mathematical models of computers, finite automata, Turing machines, counter machines, push-down machines, computational complexity.

    Terms: Fall 2013

    Instructors: Prakash Panangaden (Fall)

    • 3 hours
    • Prerequisite: COMP 251.
  • COMP 362 Honours Algorithm Design (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2014

    Instructors: Bruce Alan Reed (Winter)

    • 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.
  • MATH 235 Algebra 1 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Henri Darmon (Fall)

    • Fall
    • 3 hours lecture; 1 hour tutorial
    • Prerequisite: MATH 133 or equivalent
  • MATH 242 Analysis 1 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : A rigorous presentation of sequences and of real numbers and basic properties of continuous and differentiable functions on the real line.

    Terms: Fall 2013

    Instructors: Ivo Klemes, Stephen W Drury (Fall)

    • Fall
    • Prerequisite: MATH 141
  • MATH 247 Honours Applied Linear Algebra (3 credits) **

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Winter 2014

    Instructors: Axel W Hundemer (Winter)

    • 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
  • MATH 248 Honours Advanced Calculus (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Partial derivatives; implicit functions; Jacobians; maxima and minima; Lagrange multipliers. Scalar and vector fields; orthogonal curvilinear coordinates. Multiple integrals; arc length, volume and surface area. Line integrals; Green's theorem; the divergence theorem. Stokes' theorem; irrotational and solenoidal fields; applications.

    Terms: Fall 2013

    Instructors: Pengfei Guan (Fall)

    • Fall and Winter and Summer
    • Prerequisites: MATH 133 and MATH 222 or consent of Department.
    • Restriction: Intended for Honours Mathematics, Physics and Engineering students
    • Restriction: Not open to students who have taken or are taking MATH 314
  • MATH 251 Honours Algebra 2 (3 credits) **

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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 self-adjoint operators.

    Terms: Winter 2014

    Instructors: Henri Darmon (Winter)

    • Winter
    • Prerequisites: MATH 235 or permission of the Department
    • Restriction: Not open to students who are taking or have taken MATH 247
  • MATH 255 Honours Analysis 2 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Series of functions including power series. Riemann integration in one variable. Elementary functions.

    Terms: Winter 2014

    Instructors: Stephen W Drury (Winter)

    • Winter
    • Prerequisites: MATH 242 or permission of the Department
  • MATH 356 Honours Probability (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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, uni-variate transformations. Random vectors, independence, correlation, multivariate transformations. Conditional distributions, conditional expectation.Modes of stochastic convergence, laws of large numbers, Central Limit Theorem.

    Terms: Fall 2013

    Instructors: Abbas Khalili Mahmoudabadi (Fall)

    • Fall
    • Prerequisite: MATH 255 or MATH 243
    • Restriction: Not open to students who have taken or are taking MATH 323
  • MATH 357 Honours Statistics (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Data analysis. Estimation and hypothesis testing. Power of tests. Likelihood ratio criterion. The chi-squared goodness of fit test. Introduction to regression analysis and analysis of variance.

    Terms: Winter 2014

    Instructors: David B Wolfson (Winter)

    • Winter
    • Prerequisite: MATH 356 or equivalent
    • Restriction: Not open to students who have taken or are taking MATH 324
  • MATH 533 Honours Regression and Analysis of Variance (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : This course consists of the lectures of MATH 423 but will be assessed at the 500 level.

    Terms: Fall 2013

    Instructors: Abbas Khalili Mahmoudabadi (Fall)

    • Prerequisites: MATH 357, MATH 247 or MATH 251.
    • Restriction: Not open to have taken or are taking MATH 423.
    • Note: An additional project or projects assigned by the instructor that require a more detailed treatment of the major results and concepts covered in MATH 423.

Complementary Courses (30 credits)

15 credits in Mathematics selected as follows:

3 credits selected from:

  • MATH 387 Honours Numerical Analysis (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Error analysis. Numerical solutions of equations by iteration. Interpolation. Numerical differentiation and integration. Introduction to numerical solutions of differential equations.

    Terms: Winter 2014

    Instructors: Antony Raymond Humphries (Winter)

    • 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.
  • MATH 397 Honours Matrix Numerical Analysis (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: This course is not scheduled for the 2013-2014 academic year.

    Instructors: There are no professors associated with this course for the 2013-2014 academic year.

    • Winter
    • Prerequisites: MATH 251 or MATH 247, COMP 202 or permission of the instructor.

At least 8 credits selected from:

  • MATH 523 Generalized Linear Models (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Modern discrete data analysis. Exponential families, orthogonality, link functions. Inference and model selection using analysis of deviance. Shrinkage (Bayesian, frequentist viewpoints). Smoothing. Residuals. Quasi-likelihood. Contingency tables: logistic regression, log-linear models. Censored data. Applications to current problems in medicine, biological and physical sciences. R software.

    Terms: Winter 2014

    Instructors: Johanna Neslehova (Winter)

    • Winter
    • Prerequisite: MATH 423
    • Restriction: Not open to students who have taken MATH 426
  • MATH 524 Nonparametric Statistics (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Distribution free procedures for 2-sample problem: Wilcoxon rank sum, Siegel-Tukey, Smirnov tests. Shift model: power and estimation. Single sample procedures: Sign, Wilcoxon signed rank tests. Nonparametric ANOVA: Kruskal-Wallis, Friedman tests. Association: Spearman's rank correlation, Kendall's tau. Goodness of fit: Pearson's chi-square, likelihood ratio, Kolmogorov-Smirnov tests. Statistical software packages used.

    Terms: This course is not scheduled for the 2013-2014 academic year.

    Instructors: There are no professors associated with this course for the 2013-2014 academic year.

    • Fall
    • Prerequisite: MATH 324 or equivalent
    • Restriction: Not open to students who have taken MATH 424
  • MATH 525 Sampling Theory and Applications (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Russell Steele (Fall)

    • Prerequisite: MATH 324 or equivalent
    • Restriction: Not open to students who have taken MATH 425
  • MATH 556 Mathematical Statistics 1 (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Distribution theory, stochastic models and multivariate transformations. Families of distributions including location-scale 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.

    Terms: Fall 2013

    Instructors: Johanna Neslehova (Fall)

    • Fall
    • Prerequisite: MATH 357 or equivalent
  • MATH 557 Mathematical Statistics 2 (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Sampling theory (including large-sample theory). Likelihood functions and information matrices. Hypothesis testing, estimation theory. Regression and correlation theory.

    Terms: Winter 2014

    Instructors: Masoud Asgharian-Dastenaei (Winter)

    • Winter
    • Prerequisite: MATH 556

The remaining Mathematics credits selected from:

** MATH 578 and COMP 540 cannot both be taken for program credit.

  • MATH 350 Graph Theory and Combinatorics (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Graph models. Graph connectivity, planarity and colouring. Extremal graph theory. Matroids. Enumerative combinatorics and listing.

    Terms: Fall 2013

    Instructors: Sergey Norin (Fall)

    • Prerequisites: MATH 235 or MATH 240 and MATH 251 or MATH 223.
    • Restrictions: Not open to students who have taken or are taking MATH 343 or MATH 340.
    • Intended for students in mathematics or computer science honours programs.
  • MATH 352 Problem Seminar (1 credit)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Sergey Norin (Fall)

    • 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.
  • MATH 354 Honours Analysis 3 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Introduction to metric spaces. Multivariable differential calculus, implicit and inverse function theorems.

    Terms: Fall 2013

    Instructors: Vojkan Jaksic (Fall)

    • Fall
    • Prerequisite: MATH 255 or equivalent
  • MATH 355 Honours Analysis 4 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Lebesque measure, integration and Fubini's theorem. Abstract measure and integration. Convergence theorems. Introduction to Hilbert spaces, L_2 spaces, Fourier series. Fourier integrals (if time allows).

    Terms: Winter 2014

    Instructors: Vojkan Jaksic (Winter)

    • Winter
    • Prerequisite: MATH 354 or equivalent.
  • MATH 545 Introduction to Time Series Analysis (4 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    Mathematics & Statistics (Sci) : Stationary processes; estimation and forecasting of ARMA models; non-stationary and seasonal models; state-space models; financial time series models; multivariate time series models; introduction to spectral analysis; long memory models.

    Terms: This course is not scheduled for the 2013-2014 academic year.

    Instructors: There are no professors associated with this course for the 2013-2014 academic year.

    • Prerequisite: MATH 324 or MATH 357 or equivalent
  • MATH 578 Numerical Analysis 1 (4 credits) **

    Offered by: Mathematics and Statistics (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Jean-Christophe Nave (Fall)

    • Fall
    • Prerequisites: MATH 247 or MATH 251; and MATH 387; or permission of the instructor.

15 credits in Computer Science selected as follows:

At least 6 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 2014

    Instructors: Joelle Pineau (Winter)

    • 3 hours
    • Prerequisites: (COMP 206 or ECSE 321) and COMP 251
  • COMP 462 Computational Biology Methods (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Jérôme Waldispuhl (Fall)

    • 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.
  • COMP 526 Probabilistic Reasoning and AI (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Belief networks, Utility theory, Markov Decision Processes and Learning Algorithms.

    Terms: This course is not scheduled for the 2013-2014 academic year.

    Instructors: There are no professors associated with this course for the 2013-2014 academic year.

    • 3 hours
    • Prerequisites: COMP 206, COMP 360, COMP 424 and MATH 323
  • COMP 540 Matrix Computations (3 credits) **

    Offered by: Computer Science (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Xiao-Wen Chang (Fall)

    • 3 hours
    • Prerequisite: MATH 327 or COMP 350
  • COMP 547 Cryptography and Data Security (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : This course presents an in-depth 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.

    Terms: Winter 2014

    Instructors: Claude Crepeau (Winter)

    • 3 hours
    • Prerequisites: COMP 360 or COMP 362, MATH 323.
  • COMP 552 Combinatorial Optimization (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: Frederick Shepherd (Fall)

    • 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.
  • COMP 564 Computational Gene Regulation (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : This course examines computational problems related to gene regulation at the mRNA and protein levels. With respect to mRNA expression, topics include microarray analysis, SNP detection, and the inference of genetic networks. With respect to protein expression, topics include peptide sequencing, peptide identification, and the interpretation of interaction maps.

    Terms: This course is not scheduled for the 2013-2014 academic year.

    Instructors: There are no professors associated with this course for the 2013-2014 academic year.

    • 3 hours
    • Prerequisite: COMP 462.
  • COMP 566 Discrete Optimization 1 (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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.

    Terms: This course is not scheduled for the 2013-2014 academic year.

    Instructors: There are no professors associated with this course for the 2013-2014 academic year.

    • 3 hours
    • Prerequisites: COMP 360 and MATH 223
  • COMP 567 Discrete Optimization 2 (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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.

    Terms: Fall 2013

    Instructors: David Avis (Fall)

    • 3 hours
    • Prerequisites: COMP 566 or MATH 417

The remaining Computer Science credits are selected from COMP courses at the 300 level or above excluding COMP 396 and COMP 431.

Faculty of Science—2013-2014 (last updated Aug. 21, 2013) (disclaimer)