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Applied Mathematics Major
Applied mathematics traditionally consists of areas of mathematics which are closely related to the physical sciences and engineering, but nowadays sophisticated mathematical tools are used across many disciplines, and applied mathematics has become increasingly computationally oriented.
The Department of Mathematics offers an applied mathematics major program. Students interested in applied mathematics may also wish to consider the joint honours program in mathematics and computer science, and the mathematical physics honours program, both of which include a substantial number of applied mathematics courses.
Prerequisite Grade Requirement
To enroll in a course offered by the Department of Mathematics, a student must obtain a grade of C- or better in each prerequisite course. Some courses may require higher prerequisite grades. Check the MATH course’s Calendar description for details.
Students will not normally be permitted to enroll in any course for which a D grade or lower was obtained in any prerequisite. No student may complete, for further credit, any course offered by the Department of Mathematics which is a prerequisite for a course the student has already completed with a grade of C- or higher, without permission of the department.
Program Requirements
Students complete 120 units, as specified below.
Lower Division Requirements
Students complete the following:
both of
An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a high-level language, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. Treatment is informal and programming is presented as a problem-solving tool. Prerequisite: BC Math 12 or equivalent is recommended. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Hazra Imran |
May 8 β Aug 4, 2023: Mon, 8:30β10:20 a.m.
May 8 β Aug 4, 2023: Wed, 8:30β9:20 a.m. |
Burnaby Burnaby |
A second course in computing science and programming intended for students studying mathematics, statistics or actuarial science and suitable for students who already have some background in computing science and programming. Topics include: a review of the basic elements of programming: use and implementation of elementary data structures and algorithms; fundamental algorithms and problem solving; basic object-oriented programming and software design; computation and computability and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120, with a minimum grade of C-. Students with credit for CMPT 125 or 135 may not take this course for further credit. Quantitative.
(Students transferring into a math program should contact the math undergraduate advisor if they have already completed equivalent courses.)
or both of
An introduction to computing science and computer programming, using a systems oriented language, such as C or C++. This course introduces basic computing science concepts. Topics will include: elementary data types, control structures, functions, arrays and strings, fundamental algorithms, computer organization and memory management. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157, with a minimum grade of C-). Students with credit for CMPT 102, 120, 128 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.
A second course in systems-oriented programming and computing science that builds upon the foundation set in CMPT 130 using a systems-oriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to object-oriented programming (OOP); techniques for designing and testing programs; use and implementation of elementary data structures and algorithms; introduction to embedded systems programming. Prerequisite: CMPT 130 with a minimum grade of C-. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.
and all of
Using a mathematical software package for doing calculations in linear algebra. Development of computer models that analyze and illustrate applications of linear algebra. All calculations and experiments will be done in the Matlab software package. Topics include: large-scale matrix calculations, experiments with cellular automata, indexing, searching and ranking pages on the internet, population models, data fitting and optimization, image analysis, and cryptography. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and one of MATH 150, 151, 154 or 157 and one of MATH 232 or 240. MATH 232 or 240 can be taken as corequisite. Students in excess of 80 units may not take MACM 203 for further credit. Quantitative.
Using a mathematical software package for doing computations from calculus. Development of computer models that analyze and illustrate applications of calculus. All calculations and experiments will be done in the Maple software package. Topics include: graphing functions and data, preparing visual aids for illustrating mathematical concepts, integration, Taylor series, numerical approximation methods, 3D visualization of curves and surfaces, multi-dimensional optimization, differential equations and disease spread models. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and MATH 251. MATH 251 can be taken as a corequisite. Students in excess of 80 units may not take MACM 204 for further credit. Quantitative.
Rectangular, cylindrical and spherical coordinates. Vectors, lines, planes, cylinders, quadric surfaces. Vector functions, curves, motion in space. Differential and integral calculus of several variables. Vector fields, line integrals, fundamental theorem for line integrals, Green's theorem. Prerequisite: MATH 152 with a minimum grade of C-; or MATH 155 or MATH 158 with a grade of at least B. Recommended: It is recommended that MATH 240 or 232 be taken before or concurrently with MATH 251. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Hansol Park |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 1:30β2:20 p.m.
|
Burnaby |
|
Justin Chan |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 9:30β10:20 a.m.
|
Surrey |
|
OP01 | TBD | ||
OP02 | TBD |
Vector calculus, divergence, gradient and curl; line, surface and volume integrals; conservative fields, theorems of Gauss, Green and Stokes; general curvilinear coordinates and tensor notation. Introduction to orthogonality of functions, orthogonal polynomials and Fourier series. Prerequisite: MATH 240 or 232, and 251, all with a minimum grade of C-. MATH 240 or 232 may be taken concurrently. Students with credit for MATH 254 may not take MATH 252 for further credit. Quantitative.
First-order differential equations, second- and higher-order linear equations, series solutions, introduction to Laplace transform, systems and numerical methods, applications in the physical, biological and social sciences. Prerequisite: MATH 152 with a minimum grade of C-; or MATH 155 or 158, with a grade of at least B; MATH 232 or 240, with a minimum grade of C-. Students with credit for MATH 310 may not take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Stephen Choi |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 12:30β1:20 p.m.
|
Burnaby |
|
D101 |
May 8 β Aug 4, 2023: Mon, 4:30β5:20 p.m.
|
Burnaby |
|
D102 |
May 8 β Aug 4, 2023: Tue, 10:30β11:20 a.m.
|
Burnaby |
|
D103 |
May 8 β Aug 4, 2023: Tue, 11:30 a.m.β12:20 p.m.
|
Burnaby |
|
D104 |
May 8 β Aug 4, 2023: Tue, 9:30β10:20 a.m.
|
Burnaby |
|
D105 |
May 8 β Aug 4, 2023: Mon, 5:30β6:20 p.m.
|
Burnaby |
|
Justin Chan |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 12:30β1:20 p.m.
|
Surrey |
|
D401 |
May 8 β Aug 4, 2023: Wed, 2:30β3:20 p.m.
|
Surrey |
|
D402 |
May 8 β Aug 4, 2023: Wed, 3:30β4:20 p.m.
|
Surrey |
Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158, with a minimum grade of C-. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Wei Lin |
May 8 β Aug 4, 2023: Wed, 11:30 a.m.β12:20 p.m.
May 8 β Aug 4, 2023: Fri, 10:30 a.m.β12:20 p.m. |
Burnaby Burnaby |
|
Gamage Perera |
Online | ||
OP01 | TBD |
and one of
Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Topics as for Math 151 with a more extensive review of functions, their properties and their graphs. Recommended for students with no previous knowledge of Calculus. In addition to regularly scheduled lectures, students enrolled in this course are encouraged to come for assistance to the Calculus Workshop (Burnaby), or Math Open Lab (Surrey). Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B-, or achieving a satisfactory grade on the Ά‘ΟγΤ°AV Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
MacKenzie Carr |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 1:30β2:20 p.m.
|
Burnaby |
|
D101 |
May 8 β Aug 4, 2023: Tue, 8:30β9:20 a.m.
|
Burnaby |
|
D102 |
May 8 β Aug 4, 2023: Tue, 9:30β10:20 a.m.
|
Burnaby |
|
D103 |
May 8 β Aug 4, 2023: Tue, 10:30β11:20 a.m.
|
Burnaby |
|
OP01 | TBD |
Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Logarithmic and exponential functions, trigonometric functions, inverse functions. Limits, continuity, and derivatives. Techniques of differentiation, including logarithmic and implicit differentiation. The Mean Value Theorem. Applications of differentiation including extrema, curve sketching, Newton's method. Introduction to modeling with differential equations. Polar coordinates, parametric curves. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least A, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Ά‘ΟγΤ°AV Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.
Designed for students specializing in the life sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications, integration, and differential equations; mathematical models of biological processes and their implementation and analysis using software. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C-, or achieving a satisfactory grade on the Ά‘ΟγΤ°AV Calculus Readiness Test. Students with credit for either MATH 150, 151 or 157 may not take MATH 154 for further credit. Quantitative.
Designed for students specializing in business or the social sciences. Topics include: limits, growth rate and the derivative; logarithmic, exponential and trigonometric functions and their application to business, economics, optimization and approximation methods; introduction to functions of several variables with emphasis on partial derivatives and extrema. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Ά‘ΟγΤ°AV Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Mahsa Faizrahnemoon |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 11:30 a.m.β12:20 p.m.
|
Burnaby |
|
OP01 | TBD |
and one of
Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. First-order separable differential equations and growth models. Sequences and series, series tests, power series, convergence and applications of power series. Prerequisite: MATH 150 or 151, with a minimum grade of C-; or MATH 154 or 157 with a grade of at least B. Students with credit for MATH 155 or 158 may not take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Alexander Rutherford |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 8:30β9:20 a.m.
|
Burnaby |
|
OP01 | TBD |
Designed for students specializing in the life sciences. Topics include: vectors and matrices, partial derivatives, multi-dimensional integrals, systems of differential equations, compartment models, graphs and networks, and their applications to the life sciences; mathematical models of multi-component biological processes and their implementation and analysis using software. Prerequisite: MATH 150, 151 or 154, with a minimum grade of C-; or MATH 157 with a grade of at least B. Students with credit for MATH 152 or 158 may not take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Vijaykumar Singh |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 8:30β9:20 a.m.
|
Burnaby |
|
OPO1 | TBD |
Designed for students specializing in business or the social sciences. Topics include: theory of integration, integration techniques, applications of integration; functions of several variables with emphasis on double and triple integrals and their applications; introduction to differential equations with emphasis on some special first-order equations and their applications; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157, with a minimum grade of C-. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.
and one of
Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151 or MACM 101, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 may not take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Navpreet Kaur |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 1:30β2:20 p.m.
|
Surrey |
|
OP01 | TBD |
Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151 or MACM 101, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 232 cannot take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Jonathan Jedwab |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 11:30 a.m.β12:20 p.m.
|
Burnaby |
|
D101 |
May 8 β Aug 4, 2023: Thu, 9:30β10:20 a.m.
|
Burnaby |
|
D102 |
May 8 β Aug 4, 2023: Thu, 2:30β3:20 p.m.
|
Burnaby |
|
D103 |
May 8 β Aug 4, 2023: Thu, 3:30β4:20 p.m.
|
Burnaby |
and at least one of
Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; object-oriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and (CMPT 125, CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252), all with a minimum grade of C-. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Toby Donaldson |
May 8 β Aug 4, 2023: Tue, 12:30β2:20 p.m.
May 8 β Aug 4, 2023: Fri, 12:30β1:20 p.m. |
Burnaby Burnaby |
|
D101 |
May 8 β Aug 4, 2023: Wed, 11:30 a.m.β12:20 p.m.
|
Burnaby |
|
D102 |
May 8 β Aug 4, 2023: Wed, 11:30 a.m.β12:20 p.m.
|
Burnaby |
|
D103 |
May 8 β Aug 4, 2023: Thu, 9:30β10:20 a.m.
|
Burnaby |
|
D104 |
May 8 β Aug 4, 2023: Thu, 9:30β10:20 a.m.
|
Burnaby |
|
D105 |
May 8 β Aug 4, 2023: Thu, 10:30β11:20 a.m.
|
Burnaby |
|
D106 |
May 8 β Aug 4, 2023: Thu, 10:30β11:20 a.m.
|
Burnaby |
|
D107 |
May 8 β Aug 4, 2023: Wed, 12:30β1:20 p.m.
|
Burnaby |
|
D108 |
May 8 β Aug 4, 2023: Wed, 12:30β1:20 p.m.
|
Burnaby |
|
John Edgar |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 8:30β9:20 a.m.
|
Surrey |
|
D201 |
May 8 β Aug 4, 2023: Mon, 10:30β11:20 a.m.
|
Surrey |
|
D202 |
May 8 β Aug 4, 2023: Mon, 10:30β11:20 a.m.
|
Surrey |
|
D203 |
May 8 β Aug 4, 2023: Mon, 11:30 a.m.β12:20 p.m.
|
Surrey |
|
D204 |
May 8 β Aug 4, 2023: Mon, 11:30 a.m.β12:20 p.m.
|
Surrey |
|
D205 |
May 8 β Aug 4, 2023: Mon, 12:30β1:20 p.m.
|
Surrey |
|
D206 |
May 8 β Aug 4, 2023: Mon, 12:30β1:20 p.m.
|
Surrey |
|
D207 |
May 8 β Aug 4, 2023: Mon, 1:30β2:20 p.m.
|
Surrey |
|
D208 |
May 8 β Aug 4, 2023: Mon, 1:30β2:20 p.m.
|
Surrey |
Fundamental electrical circuit quantities, and circuit elements; circuits laws such as Ohm law, Kirchoff's voltage and current laws, along with series and parallel circuits; operational amplifiers; network theorems; nodal and mesh methods; analysis of natural and step response of first (RC and RL), as well as second order (RLC) circuits; real, reactive and rms power concepts. In addition, the course will discuss the worker safety implications of both electricity and common laboratory practices such as soldering. Prerequisite: (PHYS 121 or PHYS 126 or PHYS 141), ENSC 120, MATH 232 and (MATH 260 or MATH 310), all with a minimum grade of C-. MATH 260 may be taken concurrently. Students with credit for MSE 250 or SEE 230 cannot take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
May 8 β Aug 4, 2023: Tue, Thu, 2:30β4:20 p.m.
|
Burnaby |
||
LA01 |
May 8 β Aug 4, 2023: Mon, 2:30β4:50 p.m.
|
Burnaby |
|
LA02 |
May 8 β Aug 4, 2023: Mon, 8:30β10:50 a.m.
|
Burnaby |
This course will cover the following topics: fundamental electrical circuit quantities, and circuit elements; circuits laws such as Ohm law, Kirchoff's voltage and current laws, along with series and parallel circuits; operational amplifiers; network theorems; nodal and mesh methods; analysis of natural and step response of first (RC and RL), as well as second order (RLC) circuits; real, reactive and rms power concepts. In addition, the course will discuss the worker safety implications of both electricity and common laboratory practices such as soldering. Prerequisite: PHYS 141 or (PHYS 121 and 131), and MATH 232 and (MATH 260 or MATH 310). (MATH 260 or MATH 310) may be taken concurrently. Students with credit for SEE 230 or ENSC 220 may not take MSE 250 for further credit. Quantitative.
An intermediate mechanics course covering kinematics, dynamics, calculus of variations and Lagrange's equations, non-inertial reference frames, central forces and orbits, and rigid body motion. Prerequisite: MATH 251; MATH 232 or MATH 240; PHYS 255 or ENSC 380. All prerequisite courses require a minimum grade of C-. Recommended Corequisite: MATH 260 or MATH 310. Quantitative.
The concepts of quantum mechanics introduced through two-level systems and explored in a way that requires only familiarity with general concepts of linear algebra. Introduction to concepts in classical and quantum information theory, bits and qubits, quantum dynamics, quantum communication and cryptography, and quantum circuits. Prerequisite: Either MATH 232 or MATH 240, with a minimum grade of C-. Quantitative.
This course is a continuation of STAT 270. Review of probability models. Procedures for statistical inference using survey results and experimental data. Statistical model building. Elementary design of experiments. Regression methods. Introduction to categorical data analysis. Prerequisite: STAT 270 and one of MATH 152, MATH 155, or MATH 158, all with a minimum grade of C-. Quantitative.
and an additional six units from the Faculty of Science outside of the departments of Mathematics and Statistics and Actuarial Science and excluding PHYS 100, BISC 100 and CHEM 110/111.
+ The following substitutions are also permitted.
They may not also be used to satisfy the upper division requirements below.
MACM 409 - Numerical Linear Algebra: Algorithms, Implementation and Applications (3) for MACM 203.
MACM 401 - Introduction to Computer Algebra (3) for MACM 204.
MACM 442 - Cryptography (3) for MACM 204.
* strongly recommended
** with a B grade or better
Upper Division Requirements
Students complete a minimum of 30 units, including all of
A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Jane MacDonald |
May 8 β Aug 4, 2023: Mon, Wed, Fri, 10:30β11:20 a.m.
|
Burnaby |
|
D101 |
May 8 β Aug 4, 2023: Wed, 2:30β3:20 p.m.
|
Burnaby |
|
D102 |
May 8 β Aug 4, 2023: Wed, 3:30β4:20 p.m.
|
Burnaby |
|
D103 |
May 8 β Aug 4, 2023: Wed, 4:30β5:20 p.m.
|
Burnaby |
|
D104 |
May 8 β Aug 4, 2023: Thu, 9:30β10:20 a.m.
|
Burnaby |
|
D105 |
May 8 β Aug 4, 2023: Thu, 10:30β11:20 a.m.
|
Burnaby |
|
D106 |
May 8 β Aug 4, 2023: Thu, 11:30 a.m.β12:20 p.m.
|
Burnaby |
|
D107 |
May 8 β Aug 4, 2023: Wed, 4:30β5:20 p.m.
|
Burnaby |
Fourier series, ODE boundary and eigenvalue problems. Separation of variables for the diffusion wave and Laplace/Poisson equations. Polar and spherical co-ordinate systems. Symbolic and numerical computing, and graphics for PDEs. Prerequisite: MATH 260 or MATH 310, with a minimum grade of C-; and one of MATH 251 with a grade of B+, or one of MATH 252 or 254, with a minimum grade of C-. Quantitative.
First-order linear equations, the method of characteristics. The wave equation. Harmonic functions, the maximum principle, Green's functions. The heat equation. Distributions and transforms. Higher dimensional eigenvalue problems. An introduction to nonlinear equations. Burgers' equation and shock waves. Prerequisite: (MATH 260 or MATH 310) and one of MATH 314, MATH 320, MATH 322, PHYS 384, all with a minimum grade of C-. An alternative to the above prerequisite is both of (MATH 252 or MATH 254) and (MATH 260 or MATH 310), both with grades of at least A-. Quantitative.
and at least one of
An introduction to probability from the rigorous point of view. Random variables. Generating functions. Convergence of random variables. The strong law of large numbers and the central limit theorem. Stochastic processes. Stationary process and martingales. Prerequisite: MATH 242 and (MATH 348 or STAT 380), all with a minimum grade of C-.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Paul Tupper |
May 8 β Aug 4, 2023: Mon, 12:30β2:20 p.m.
May 8 β Aug 4, 2023: Wed, 1:30β2:20 p.m. |
Burnaby Burnaby |
Incompressible fluid flow phenomena: kinematics and equations of motion, viscous flow and boundary layer theory, potential flow, water waves. Aerodynamics. Prerequisite: One of MATH 314, MATH 418, PHYS 384, with a minimum grade of C-. An alternative to the above prerequisite is both of MATH 251 and (MATH 260 or MATH 310), both with grades of at least B+. Quantitative.
Stability and bifurcation in continuous and discrete dynamical systems, with applications. The study of the local and global behaviour of linear and nonlinear systems, including equilibria and periodic orbits, phase plane analysis, conservative systems, limit cycles, the Poincare-Bendixson theorem, Hopf bifurcation and an introduction to chaos. Prerequisite: MATH 310 with a minimum grade of C-. Quantitative.
An exploration of the mathematics of data science. Analysis of the foundations of algorithms currently used in the field. Potential topics to be covered include: machine learning, compressed sensing, clustering, randomized numerical linear algebra, complex networks and random graph models. Students may repeat this course for further credit under a different topic. Prerequisite: MATH 242, MATH 240 or MATH 232 and STAT 270, all with a minimum grade of C-.
and at least two of
Data structures and algorithms for mathematical objects. Topics include long integer arithmetic, computing polynomial greatest common divisors, the fast Fourier transform, Hensel's lemma and p-adic methods, differentiation and simplification of formulae, and polynomial factorization. Students will use a computer algebra system such as Maple for calculations and programming. Prerequisite: CMPT 307 or ((MATH 340 or MATH 342) and (CMPT 225 or MACM 204)). Quantitative.
Development of numerical methods for solving linear algebra problems at the heart of many scientific computing problems. Mathematical foundations for the use, implementation and analysis of the algorithms used for solving many optimization problems and differential equations. Prerequisite: MATH 251, MACM 316, programming experience. Quantitative.
Linear programming modelling. The simplex method and its variants. Duality theory. Post-optimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Prerequisite: MATH 150, 151, 154, or 157 and MATH 240 or 232, all with a minimum grade of C-. Quantitative.
Theoretical and computational methods for investigating the minimum of a function of several real variables with and without inequality constraints. Applications to operations research, model fitting, and economic theory. Prerequisite: MATH 232 or 240, and 251, all with a minimum grade of C-. Quantitative.
Linear Algebra. Vector space and matrix theory. Prerequisite: MATH 340 or 332, with a minimum grade of C- or permission of the instructor. Students with credit for MATH 438 may not take this course for further credit. Quantitative.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Imin Chen Jaskaran Kaur |
May 8 β Aug 4, 2023: Wed, 3:30β4:20 p.m.
May 8 β Aug 4, 2023: Fri, 2:30β4:20 p.m. |
Burnaby Burnaby |
|
D102 |
May 8 β Aug 4, 2023: Wed, 12:30β1:20 p.m.
|
Burnaby |
Structures and algorithms, generating elementary combinatorial objects, counting (integer partitions, set partitions, Catalan families), backtracking algorithms, branch and bound, heuristic search algorithms. Prerequisite: MACM 201 (with a grade of at least B-). Recommended: knowledge of a programming language. Quantitative.
Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B-). Quantitative.
Review of the basics of probability, including sample space, random variables, expectation and conditioning. Applications of Markov chains, the exponential distribution and the Poisson process from science and industry. Applications may include inventory theory, queuing, forecasting, scheduling and simulation. Prerequisite: STAT 270 and (MATH 232 or MATH 240), all with a minimum grade of C-. Quantitative.
Convergence in Euclidean spaces, Fourier series and their convergence, Legendre polynomials, Hermite and Laguerre polynomials. Prerequisite: MATH 232 or 240 and one of MATH 314, 320, 322, PHYS 384, all with a minimum grade of C-. Students with credit for MATH 420 or MATH 719 may not complete this course for further credit. Quantitative.
Metric spaces, normed vector spaces, measure and integration, an introduction to functional analysis. Prerequisite: MATH 320 with a minimum grade of C-. Quantitative.
An introduction to probability from the rigorous point of view. Random variables. Generating functions. Convergence of random variables. The strong law of large numbers and the central limit theorem. Stochastic processes. Stationary process and martingales. Prerequisite: MATH 242 and (MATH 348 or STAT 380), all with a minimum grade of C-.
Section | Instructor | Day/Time | Location |
---|---|---|---|
Paul Tupper |
May 8 β Aug 4, 2023: Mon, 12:30β2:20 p.m.
May 8 β Aug 4, 2023: Wed, 1:30β2:20 p.m. |
Burnaby Burnaby |
Incompressible fluid flow phenomena: kinematics and equations of motion, viscous flow and boundary layer theory, potential flow, water waves. Aerodynamics. Prerequisite: One of MATH 314, MATH 418, PHYS 384, with a minimum grade of C-. An alternative to the above prerequisite is both of MATH 251 and (MATH 260 or MATH 310), both with grades of at least B+. Quantitative.
Stability and bifurcation in continuous and discrete dynamical systems, with applications. The study of the local and global behaviour of linear and nonlinear systems, including equilibria and periodic orbits, phase plane analysis, conservative systems, limit cycles, the Poincare-Bendixson theorem, Hopf bifurcation and an introduction to chaos. Prerequisite: MATH 310 with a minimum grade of C-. Quantitative.
An exploration of the mathematics of data science. Analysis of the foundations of algorithms currently used in the field. Potential topics to be covered include: machine learning, compressed sensing, clustering, randomized numerical linear algebra, complex networks and random graph models. Students may repeat this course for further credit under a different topic. Prerequisite: MATH 242, MATH 240 or MATH 232 and STAT 270, all with a minimum grade of C-.
The topics included in this course will vary from term to term depending on faculty availability and student interest. Prerequisite: Will be specified according to the particular topic or topics offered under this course number.
Central forces, rigid body motion, small oscillations. Lagrangian and Hamiltonian formulations of mechanics. Prerequisite: PHYS 384 or permission of the department. Non-physics majors may enter with MATH 252; MATH 260 or MATH 310; PHYS 211. All prerequisite courses require a minimum grade of C-. Quantitative.
Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Prerequisite: STAT 330, or all of: STAT 285, MATH 208W, and MATH 251, all with a minimum grade of C-. Quantitative.
and one additional upper division MATH or MACM course, or any pre-approved quantitative upper division course offered by the Faculties of Applied Sciences, Arts and Social Sciences, Beedie School of Business or Faculty of Science. This course, if other than MATH or MACM, must be pre-approved by a department advisor. Students are encouraged to explore the option of completing courses outside the department and to discuss possibilities with a department advisor. Choices from the third group ("at least two of") must not include the course used to satisfy the second group ("at least one of"). At least three of the courses used to satisfy the upper division requirements must be at the 400 division.
NOTE: Ά‘ΟγΤ°AV students accepted in the accelerated master’s within the Department of Mathematics may apply a maximum of 10 graduate course units, taken while completing the bachelor's degree, towards the upper division electives of the bachelor's program and the requirements of the master's degree. For more information go to: /gradstudies/apply/programs/accelerated-masters.html.
Other Requirements
At least 44 of the units must be at the upper division. In the courses used to satisfy the upper division requirements, a grade point average (GPA) of at least 2.00 is required. In addition, University regulations require a cumulative GPA of at least 2.00 and an upper division GPA of at least 2.00.
These averages are computed on all courses completed at the University. See Grade Point Averages Needed for Graduation.
In addition to the above requirements, students must also satisfy Faculty of Science major program requirements as follows.
University Degree Requirements
Students must also satisfy University degree requirements for degree completion.
Writing, Quantitative, and Breadth Requirements
Students admitted to Ά‘ΟγΤ°AV beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for university-wide information.
WQB Graduation Requirements
A grade of C- or better is required to earn W, Q or B credit
Requirement |
Units |
Notes | |
W - Writing |
6 |
Must include at least one upper division course, taken at Ά‘ΟγΤ°AV within the studentβs major subject | |
Q - Quantitative |
6 |
Q courses may be lower or upper division | |
B - Breadth |
18 |
Designated Breadth | Must be outside the studentβs major subject, and may be lower or upper division 6 units Social Sciences: B-Soc 6 units Humanities: B-Hum 6 units Sciences: B-Sci |
6 |
Additional Breadth | 6 units outside the studentβs major subject (may or may not be B-designated courses, and will likely help fulfil individual degree program requirements) Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas. |
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Residency Requirements and Transfer Credit
- At least half of the program's total units must be earned through Ά‘ΟγΤ°AV study.
- At least two thirds of the program's total upper division units must be earned through Ά‘ΟγΤ°AV study.
Elective Courses
In addition to the courses listed above, students should consult an academic advisor to plan the remaining required elective courses.