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Courses

A summary of each course to help with your selection.

Academic Year

Programs

Course ID

Course ID	Course
MATH 311	MATH 311 Ordinary Differential Equations Course Credits: 3 First-order differential equations, linear differential equations, Laplace transforms, systems of differential equations, non-linear systems, series solutions, applications in the physical, biological, social, and engineering sciences. Prerequisite(s): MATH 124, 250 NB: Credit is granted for only one of MATH 311 or MATH 321. Not offered every year. See department chair.
MATH 313	MATH 313 The Real Line Course Credits: 3 Introduction to principles of real analysis. Topics include rational numbers, completeness, sequences, limits, continuity, and implications to Calculus. Prerequisite(s): MATH 124, 150 NB: Credit is granted for only one of MATH 313 or MATH 323. Not offered every year. See department chair.
MATH 317	MATH 317 Scientific Computation Course Credits: 3 Symbolic and numerical computations used in scientific modelling based on Calculus and Linear Algebra, with emphasis on applications in physics and biology. Topics include error analysis, linear systems, roots of equations, interpolation, numerical differentiation, and integration. Further topics may include: eigenvalues and singular values, approximation theory, and non-linear systems. Cross-listed: CMPT 317. Prerequisite(s): MATH 124, MATH 250, and CMPT 140. NB: Credit is granted for only one of MATH/CMPT 317 and MATH/CMPT 327 and MATH/CMPT 330.
MATH 320	MATH 320 Complex Variables Course Credits: 3 Functions of a complex variable, differentiation, analytic and elementary functions, Cauchy's theorem and contour integration, Taylor and Laurent series, residues and poles, and conformal mapping. Emphasis is placed on physical applications. Prerequisite(s): MATH 223 NB: Not offered every year. See department chair.
MATH 321	MATH 321 Differential Equations Course Credits: 4 First-order differential equations, linear differential equations, Laplace transforms, systems of differential equations, non-linear systems, series solutions, introduction to partial differential equations. Special emphasis is placed on applications to physics and engineering. Cross-listed: PHYS 321 Co-requisite(s): MATH 223, 250 NB: Credit is granted for only one of MATH 311 or MATH 321.
MATH 323	MATH 323 Analysis Course Credits: 4 Sequences and induction; convergence of sequences and series; limits, continuity, and differentiability; Riemann integrals; sequences of functions and an introduction to topology. Prerequisite(s): MATH 150, 223 NB: Credit is granted for only one of MATH 313 or MATH 323.
MATH 327	MATH 327 Numerical Analysis Course Credits: 4 This course covers numerical techniques for solving problems in applied mathematics, including error analysis, roots of equations, interpolation, numerical differentiation and integration, ordinary differential equations, matrix methods and selected topics from among: eigenvalues, approximation theory, non-linear systems, boundary-value problems, numerical solution of partial differential equations. Cross-listed: CMPT 327. Prerequisite(s): MATH 223, 250; CMPT 140. (4-0) NB: Credit is granted for only one of MATH/CMPT 317 and MATH/CMPT 327 and MATH/CMPT 330.
MATH 333	MATH 333 Mathematics of Data Science Course Credits: 3 Foundational mathematical concepts underpinning theoretical frameworks in data science that depend on linear algebra and multivariable calculus, with applications chosen from machine learning, statistical inference, and data assimilation. Possible topics include matrix decompositions, gradient and multivariate chain rule, Lagrange multipliers and constrained optimization, maximum likelihood, and Bayesian estimation. Prerequisite(s): MATH 223, 250 NB: Not offered every year. See department chair.
MATH 340	MATH 340 Discrete Structures & Computing Course Credits: 3 This is a second course in the topics of pure mathematics, particularly those most commonly used in the study of Computing Science and related applications. It includes proof techniques, models of computation, formal languages, analysis of algorithms, trees and advanced general graph theory with applications, finite state and automata theory, encryption, and an elementary introduction to mathematical structures such as groups, rings, and fields. Cross-listed: CMPT 340 Prerequisite(s): CMPT 150 or MATH 150 NB: Not offered every year. See department chair.

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