is an introduction to differential calculus, including algebraic, trigonometric, exponential, logarithmic, inverse trigonometric and hyperbolic functions. Applications include kinematics, related rates problems, curve sketching and optimization.

is an introduction to integral calculus, including Riemann sums and the Fundamental Theorem of Calculus, techniques of integration, improper integrals and first order differential equations. Applications include: area between curves, volumes of solids of revolution, probability functions and modelling with differential equations.

covers topics which include elementary algebra and functions, sets, elementary probability, matrices, systems of equations, and linear programming.

covers topics which include logic, permutations, combinations, mathematical systems, elementary number theory, and geometry.

is a two-semester course which provides students with the essential prerequisite elements for the study of an introductory course in calculus, at a slower pace than MATH 1090. Topics include algebra, functions and their graphs, exponential and logarithmic functions, trigonometry, polynomials, and rational functions.

provides students with the essential prerequisite elements for the study of an introductory course in calculus. Topics include algebra, functions and their graphs, exponential and logarithmic functions, trigonometry, polynomials, and rational functions.

is an introduction to infinite sequences and series, and to the differential and integral calculus of multivariate functions. Topics include tests for the convergence of infinite series, power series, Taylor and Maclaurin series, complex numbers including Euler's formula, partial differentiation, and double integrals in Cartesian and polar coordinates.

includes the topics of Euclidean n-space, vector operations in 2- and 3-space, complex numbers, linear transformations on n-space, matrices, determinants, and systems of linear equations.

includes the topics of real and complex vector spaces, basis, dimension, change of basis, eigenvectors, inner products, and diagonalization of Hermitian matrices.

covers the following topics: simple and compound interest and discount, forces of interest and discount, equations of value, annuities and perpetuities, amortization schedules and sinking funds, bonds and other securities, contingent payments.

is a project oriented course combining mathematical investigation and technical writing. By using computer programming, graphical and typesetting tools, students will explore mathematical concepts and will produce technical reports of professional quality. The latter will combine elements of writing and graphics to convey technical ideas in a clear and concise manner.

introduces first and second order differential equations, systems of first order differential equations and Laplace transforms. These will be studied with both analytic techniques as well as using a computer algebra system to generate symbolic and numerical solutions. Applications include oscillatory motion and population and epidemic models.

covers basic concepts of mathematical reasoning: logic and quantifiers, methods of proof, sets and set operations, functions and relations, equivalence relations and partial orders, countable and uncountable sets. These concepts will be illustrated through the congruence and divisibility of integers, induction and recursion, principles of counting, permutations and combinations, the Binomial Theorem, and elementary probability.

is an introduction to Euclidean geometry of the plane. It covers the geometry of triangles and circles, including results such as the Euler line, the nine-point circle and Ceva’s theorem. It also includes straight-edge and compass constructions, isometries of the plane, the three reflections theorem, and inversions on circles.

covers descriptive statistics (including histograms, stem-and-leaf plots and box plots), elementary probability, random variables, the binomial distribution, the normal distribution, sampling distribution, estimation and hypothesis testing including both one and two sample tests, paired comparisons, correlation and regression, related applications.

is an introduction to basic statistics methods with an emphasis on applications to the sciences. Material includes descriptive statistics, elementary probability, binomial distribution, Poisson distribution, normal distribution, sampling distribution, estimation and hypothesis testing (both one and two sample cases), chi-square test, one way analysis of variance, correlation and simple linear regression.

covers the structure of the real numbers, sequences and limits, compactness, continuity, uniform continuity, differentiation, and the Mean Value Theorem.

includes a discussion of round-off error, the solution of linear systems, iterative methods for nonlinear equations, interpolation and polynomial approximation, least squares approximation, fast Fourier transform, numerical differentiation and integration, and numerical methods for initial value problems.

deals with functions of several variables. Lagrange multipliers, vector valued functions, directional derivatives, gradient, divergence, curl, transformations, Jacobians, inverse and implicit function theorems, multiple integration including change of variables using polar, cylindrical and spherical co-ordinates, Green’s theorem. Stokes’ theorem, divergence theorem, line integrals, arc length.

examines algorithms and complexity, definitions and basic properties of graphs, Eulerian and Hamiltonian chains, shortest path problems, graph colouring, planarity, trees, network flows, with emphasis on applications including scheduling problems, tournaments, and facilities design.

is an introduction to groups and group homomorphisms including cyclic groups, cosets, Lagrange's theorem, normal subgroups and quotient groups, introduction to rings and ring homomorphisms including ideals, prime and maximal ideals, quotient rings, integral domains and fields.

includes Topics such as distributions, the binomial and multinomial theorems, Stirling numbers, recurrence relations, generating functions and the inclusion-exclusion principle. Emphasis will be on applications.

is perfect numbers and primes, divisibility, Euclidean algorithm, greatest common divisors, primes and the unique factorization theorem, congruences, cryptography (secrecy systems), Euler-Fermat theorems, power residues, primitive roots, arithmetic functions, Diophantine equations, topics above in the setting of the Gaussian integers.

is basic probability concepts, combinatorial analysis, conditional probability, independence, random variable, distribution function, mathematical expectation, Chebyshev's inequality, distribution of two random variables, binomial and related distributions, Poisson, gamma, normal, bivariate normal, t, and F distributions, transformations of variables including the moment-generating function approach.

is an introduction to optimization, analytic methods for functions of one variable and for functions of several variables, classical maxima and minima, necessary and sufficient conditions, constrained optimization, equality and inequality constraints, Kuhn-Tucker conditions, introduction to the calculus of variations, linear programming, simplex algorithm.

covers two point boundary value problems, Fourier series, Sturm-Liouville theory, canonical forms, classification and solution of linear second order partial differential equations in two independent variables, separation of variable, integral transform methods.

is an introduction to population dynamics modelling and epidemiological modelling via ordinary and partial differential equations. Topics include basic non-spatial single species models, pollution models, non-spatial models of interacting populations, chemostat models, disease dynamics models, spatial population dynamics via reaction-diffusion equations, steady state solutions, modelling of invasive species, notions of critical domain size and spreading speed, extending classical models to two-compartment and spatially heterogenous settings.

is a study of the correctness and complexity of algorithms, with particular focus on algorithms important in mathematics. Topics may include sorting and binary search, string searching, integer multiplication and exponentiation, matrix multiplication, geometric problems such as closest pair of points and convex hull, probabilistic and approximative algorithms. This course discusses polynomial reductions and NP-completeness.

is an advanced course in linear algebra and matrix theory with applications in quantum information. Topics include spectral theorem, singular value decomposition, variational characterizations of eigenvalues of Hermitian matrices, vector and matrix norms, characterizations of positive definite matrices, trace inequalities and entropy.

are courses offered on a one-time basis which cover a specific mathematical topic.

starts with a brief overview of basic set theory, followed by an introduction to propositional and predicate logic and basics of model theory (models, theories, compactness theorem) and computability theory (computable and computably enumerable sets, first order arithmetic).

continues most of the topics started in 3340 with further work on distributions, recurrence relations and generating functions. Generating functions are used to solve recurrence relations in two variables. Also included is a study of Polya's theorem with applications.

is an introduction to the study of two-player strategy games of perfect information and no chance. Topics include canonical form; group and poset structure of short games; Sprague-Grundy Theory of impartial games; and monoids of games under misère play. Computer programming will be used to analyze games computationally.

includes topics which may be chosen from matchings, factorizations, adjacency matrices, eigenvalues of graphs, strongly regular graphs, independent sets and cliques, cuts and connectivity, graph products, graph homomorphisms, edge colourings, domination, and graph searching.

is a course in which, under the guidance of a faculty member, students conduct a study of an area of mathematics. Students are required to submit a report and give a presentation.

is a two-semester course that requires the student, under the supervision of a faculty member, to prepare a dissertation in an area of mathematics.  In addition to a written project, an oral presentation will be given by the student at the end of the second semester.