Spring 2026:
This course discusses mathematical models used in analytics and operations research. The basic models discussed serve as an introduction to the analysis of data and methods for optimal decision and planning. Mathematical methods and algorithms discussed include advanced linear algebra, convex optimization, and probability. These are some of the tools necessary for the data classification, machine learning, clustering and pattern recognition, and for problems in planning, resource allocation, scheduling, and ranking. The course should be useful to those students interested in operations research, business analytics, and data sciences. This class targets seniors or advanced juniors with knowledge of how to write proofs. Programming knowledge in Matlab or Python in required.
For more information see the Canvas course page.