Program course requirements are subdivided into several categories described below. The following list of courses is not exhaustive: substitutions with other similar courses within each category may be arranged. Certain requirements may be waived based on the courses taken at other institutions.
At the beginning of each academic year, the students should schedule a meeting with the Program Coordinator to work out a detailed program of courses for the coming year specialized to their needs and interests. The program course requirements are summarized in the OMS Program of Studies Form, which is updated annually by the student and the Program Coordinator.
Major Field (Core): Four PhD level courses in OM
Each year the Area offers two PhD level courses (numbered RMS3045 and RMS3046). The course topics are rotated so that different topics are offered every other year; they depend on the current research initiatives of faculty and students. Students should take both courses in each of their first two years of study. (NOTE: in the second year students should register for RMS3090, Research in OMS, since, with the exception of this course number, only one course with a specific course number can appear on the transcript.) In recent years, the following topics were offered under this category:
- OM in Services
- Logistics
- Queuing Theory
- Inventory Theory
- Combinatorial Techniques with Applications to OM
- Auction Theory
Quantitative Methods I (Stochastic Models): Minimum of Two Courses
Courses in this category are intended to give students an in-depth introduction to the areas of probability theory, stochastic processes, and stochastic optimization techniques. These courses are typically offered in the departments of Statistics (STA) and Mechanical and Industrial Engineering (MIE). Students take STA2111H and select at least 1 additional course from the following list:
- STA2111H - Graduate Probability I (*required)
- STA2211H - Graduate Probability II
- STA2006H - Applied Stochastic Processes
- STA2101H - Methods of Applied Statistics I
- STA2201H - Methods of Applied Statistics II
- STA2104H - Statistical Methods for Machine Learning and Data Mining
- STA2112H - Mathematical Statistics I
- STA2212H - Mathematical Statistics II
- MIE1605 - Stochastic Processes
- MIE1606 - Queuing Theory
- MIE1607 - Stochastic Modeling and Optimization
- MIE1615 - Stochastic Dynamic Programming
Quantitative Methods II (Mathematical Methods and Optimization Models): Minimum of Three Courses
Courses in this category are designed to provide students with the knowledge of key Operations Research methods and related mathematical techniques. These courses are typically offered in the departments of Mechanical and Industrial Engineering (MIE), Computer Science (CSC), and Economics (ECO), but can be found in other departments as well.
- MIE1620 - Mathematical Programming I
- MIE1621 - Mathematical Programming II
- MIE1606 - Integer Programming
- MIE1722 - Supply Chain Management and Logistics
- ECO1011 - Math/Stat Review (PhD), August 21-Sept 1 (*strongly recommended)
- CSC2305 - Numerical Methods for Optimization Problems
- CSC2406 - Algorithms in Graph Theory
- CIV1599 - Special Studies in Civil Engineering (Topic: Operations Research Methods for Logistical and Transportation Applications)
- Economics: 1 graduate course
Students should acquire knowledge of basic techniques of economics, including equilibrium analysis and game theory. Either ECO2020 or ECO2060 (depending on background) is recommended, but students with advanced knowledge of economics may consider other courses.
- ECO2020 - Micro Theory I (PhD)
- ECO2060 - Micro Theory I (M.A.)
- ECO2021 - Macro Theory I (PhD)
- ECO2061 - Econometrics (M.A.)
Professional Requirement: Minimum of Two Courses
These courses are designed to familiarize the students with the Operations Management function and important business applications of quantitative techniques in OM.
- RMS2405 - Supply Chain Management
- RMS2406 - OM Strategy
- RMS2415 - Service Operations
- RMS2800 - Management Science
Minor Field I: Minimum of Two Courses
A sequence of at least two advanced courses is required that are thematically linked and that are not offered by the OM Area. They can be taken either from other areas within the Rotman School or from other departments (note: courses taken within Rotman must be 2000 level or higher). Typical examples include: Finance (2 courses), Marketing (2 courses), Industrial Engineering (2 courses), Optimization Methods (2 advanced courses, not necessarily from the same department).
Minor Field II: Minimum of Two Courses
Structured similarly to Minor I. For students with M.S.-level degrees, the second minor can often be waived. For students taking two minors, one should be internal to the Rotman School and one external.
Teaching Proficiency
Students must demonstrate preparedness to serve as an instructor in business courses. This can be demonstrated through the successful completion of the course listed below, or successful hands-on teaching experience. For students with extensive prior teaching experience at the MBA level this requirement can be waived. Teaching Business in Colleges and Universities – Training Future Academics, offered annually to PhD students in Rotman (limited enrolment)