The Supplementary Minor Concentration may be taken only by students registered in the Major Concentration Computer Science or the Major Concentration Software Engineering. There may be no overlap in credits taken for this Supplementary Minor Concentration and the Major Concentration Computer Science/Software Engineering. Taken together, these constitute a program very close to the Major Computer Science offered by the Faculty of Science. Students must get their selection of courses approved by an Academic Adviser in the School of Computer Science.
Students with two programs in the same department/unit must have a third program in a different department/unit to be eligible to graduate. Please refer to the Faculty of Arts regulations for "Faculty Degree Requirements", "About Program Requirements" and "Departmental Programs" for the Multi-track System options.
Complementary Courses (18 credits)
Students may also select a maximum of 3 credits of MATH courses from the list below.
MATH 223 Linear Algebra (3 credits)
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 2019, Winter 2020
Instructors: Kelome, Djivede (Fall) Macdonald, Jeremy (Winter)
MATH 318 Mathematical Logic (3 credits)
Mathematics & Statistics (Sci) : Propositional logic: truth-tables, formal proof systems, completeness and compactness theorems, Boolean algebras; first-order logic: formal proofs, Gödel's completeness theorem; axiomatic theories; set theory; Cantor's theorem, axiom of choice and Zorn's lemma, Peano arithmetic; Gödel's incompleteness theorem.
Terms: Fall 2019
Instructors: Sabok, Marcin (Fall)
MATH 323 Probability (3 credits)
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 2019, Winter 2020, Summer 2020
Instructors: Correa, Jose Andres; Alam, Shomoita (Fall) Kelome, Djivede; Wolfson, David B (Winter)
MATH 324 Statistics (3 credits)
Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Terms: Fall 2019, Winter 2020
Instructors: Asgharian-Dastenaei, Masoud (Fall) Luo, Yu; Hurtubise, Jacques Claude (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.
MATH 340 Discrete
Mathematics (3 credits)
Mathematics & Statistics (Sci) : Discrete Mathematics and applications. Graph Theory: matchings, planarity, and colouring. Discrete probability. Combinatorics: enumeration, combinatorial techniques and proofs.
Terms: Winter 2020
Instructors: Fortier, Jérôme (Winter)