MMA 610A - Analytics Capstone Project

0 units (fi 12)(SPR/SUM, 3-0-0)

This course represents the apex of the MMA program, extending over two semesters, and offers students an immersive, real-world experience in analytics. The Analytics Capstone Project serves as a significant demonstration of the students' analytical skills and their capacity to make data-informed decisions in intricate business environments. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.

MMA 610B - Analytics Capstone Project

6 units (fi 12)(SPR/SUM, 3-0-0)

This course represents the apex of the MMA program, extending over two semesters, and offers students an immersive, real-world experience in analytics. The Analytics Capstone Project serves as a significant demonstration of the students' analytical skills and their capacity to make data-informed decisions in intricate business environments. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.

BUAN 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. Prerequisite: OM 252. Not open to students with previous credit in OM 423.

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.