Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.
Online Sync Sessions are an integral part of the online learning experience. Additional information about learning concepts and assignments may be discussed and sync sessions offer valuable opportunities for students to interact with their faculty and peers during the term. We encourage all students to attend live, but if they are unable to, sync sessions will be recorded and posted within Canvas to allow for an asynchronous model of success as well.
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 Modelers and MSDS 401-DL
Applied Statistics with R.
