Professional Degree courses in Dentistry, Education, Law, Medicine and Theology (MTS, MDiv)
Courses offered by Continuing Studies
Graduate Studies courses
* These courses are equivalent to pre-university introductory courses and may be counted for credit in the student's record, unless these courses were taken in a preliminary year. They may not be counted toward essay or breadth requirements, or used to meet modular admission requirements unless it is explicitly stated in the Senate-approved outline of the module.
1.0 course not designated as an essay course
0.5 course offered in first term
0.5 course offered in second term
0.5 course offered in first and/or second term
1.0 essay course
0.5 essay course offered in first term
0.5 essay course offered in second term
0.5 essay course offered in first and/or second term
1.0 accelerated course (8 weeks)
1.0 accelerated course (6 weeks)
0.5 graduate course offered in summer term (May - August)
0.25 course offered within a regular session
0.25 course offered in other than a regular session
1.0 accelerated course (full course offered in one term)
0.5 course offered in other than a regular session
0.5 essay course offered in other than a regular session
A course that must be successfully completed prior to registration for credit in the desired course.
A course that must be taken concurrently with (or prior to registration in) the desired course.
Courses that overlap sufficiently in course content that both cannot be taken for credit.
Many courses at Western have a significant writing component. To recognize student achievement, a number of such courses have been designated as essay courses and will be identified on the student's record (E essay full course; F/G/Z essay half-course).
A first year course that is listed by a department offering a module as a requirement for admission to the module. For admission to an Honours Specialization module or Double Major modules in an Honours Bachelor degree, at least 3.0 courses will be considered principal courses.
Decision analysis, linear programming, integer programming, statistical distributions, Markov chains, Monte Carlo simulation, queuing, discrete event simulation. Students will use a variety of tools to investigate applications including transportation networks, revenue management, production scheduling and sports analytics.
Statistical programming in a high-level language, data visualization design principles, extracting insights from data visualization, data mining and machine learning, data classification; visualization of multivariate, time-series, and hierarchical data.
Practical analytics and software tools explored through case analyses. Linear programming, statistical analysis, decision analysis, game theory, inventory analysis, queuing theory, simulation, Markovian decision model, and forecasting will be applied in a variety of scenarios.
Approaches for solving complex problems are learned and then applied to a group-based analytics consulting project done in collaboration with a not-for-profit, educational, private, or government partner.