OM 623 - Prescriptive Analytics

3 units (fi 6)(EITHER, 3-0-0)

Prescriptive analytics involves the use of data, mathematical models, and algorithms to identify optimal solutions for achieving organizational goals. This process builds on descriptive and predictive analytics, going beyond the interpretation of past events and the forecasting of future scenarios to also provide advice on the most effective actions to meet business objectives. Students acquire the skills to convert complex business problems into mathematical models, and employ Python programming and commercial solvers to derive optimal decisions. Evaluation components will consist of assignments, case studies, group projects, and two midterm exams. Prerequisites: OM 502.

OM 702 - Advanced Research Topics in Operations Management

3 units (fi 6)(EITHER, 3-0-0)

This course will provide an in-depth introduction to a particular methodology or a particular setting that is relevant to research in operations management. The topic may vary from year to year. Possible topics include optimization modeling and formulation, stochastic modeling and optimization, behavioural research in operations management, and health care operations management. The required background for students will vary depending on the topic. This course may be appropriate for some graduate students in engineering or computing science. Prerequisite: Written permission of the instructor. Approval of the Business PhD Program Director is also required for non-PhD students.

MMA 600 - Coding Bootcamp

1.5 units (fi 3)(FIRST, 18 H 2W)

Two-Week Kick Start Bootcamp: Embark on a seamless learning journey as students engage in a well-rounded experience to master two essential programming languages - Python and R. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.

MMA 601 - Business Foundations and Strategic Decision Making

3 units (fi 6)(FIRST, 3-0-0)

Students are introduced to business fundamentals in the first session followed by second session that delves deep into the dynamic world of data-driven strategy, cultivating invaluable skills in utilizing data to frame decisions effectively. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.

MMA 602 - Machine Learning For Business I

3 units (fi 6)(FIRST, 3-0-0)

The goal of the Machine Learning for Business course is to utilize machine learning techniques to transform raw data into valuable insights that can inform business strategies. This course demands a solid grasp of technical data handling methods as well as business goals. It involves an overview of various machine learning approaches, such as supervised and unsupervised learning, and their practical uses in business scenarios. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.

MMA 607 - Prescriptive Analytics

3 units (fi 6)(SECOND, 3-0-0)

This course is designed to provide a foundation of prescriptive analytics based on mathematical modeling and optimization for managerial decision-making. Topics covered in the course include decision analysis; simulation modeling; constraint programming and constraint-based optimization; network optimization and graph algorithms; optimization under uncertainty; application of prescriptive analytics techniques in various industries; integration of predictive and prescriptive analytics; and practical implementation of prescriptive analytics techniques to solve real-world problems. By the end of the course, students will have a solid understanding of prescriptive analytics techniques and their practical applications. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.

OM 423 - PRESCRIPTIVE ANALYTICS

3 units (fi 6)(EITHER, 3-0-0)

Prescriptive analytics involves the use of data, mathematical models, and algorithms to identify optimal solutions for achieving organizational goals. This process builds on descriptive and predictive analytics, going beyond the interpretation of past events and the forecasting of future scenarios to also provide advice on the most effective actions to meet business objectives. Students acquire the skills to convert complex business problems into mathematical models, and employ Python programming and commercial solvers to derive optimal decisions. Evaluation components will consist of assignments, case studies, group projects, and two midterm exams. Prerequisites: OM 252 or 352

OM 623 - Prescriptive Analytics

3 units (fi 6)(EITHER, 3-0-0)

Prescriptive analytics involves the use of data, mathematical models, and algorithms to identify optimal solutions for achieving organizational goals. This process builds on descriptive and predictive analytics, going beyond the interpretation of past events and the forecasting of future scenarios to also provide advice on the most effective actions to meet business objectives. Students acquire the skills to convert complex business problems into mathematical models, and employ Python programming and commercial solvers to derive optimal decisions. Evaluation components will consist of assignments, case studies, group projects, and two midterm exams. Prerequisites: OM 502.