Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.
MSDS 460-DL : Decision Analytics
Description
This course covers fundamental concepts, solution techniques,
modeling approaches, and applications of decision analytics. It
introduces commonly used methods of optimization, simulation and
decision analysis techniques for prescriptive analytics in
business. Students explore linear programming, network
optimization, integer linear programming, goal programming,
multiple objective optimization, nonlinear programming,
metaheuristic algorithms, stochastic simulation, queuing modeling,
decision analysis, and Markov decision processes. Students develop
a contextual understanding of techniques useful for managerial
decision support. They implement decision-analytic techniques using
a state-of-the-art analytical modeling platform. This is a problem
and project-based course.
Prerequisites: MSDS 400-DL Math for Data Scientists and MSDS
401-DL Applied Statistics with R.
