Courses Taught at WPI

Modeling and analysis of dynamic systems subject to uncertainty. Topics include design of simulation experiments, probability review, output analyses, data structures and discrete-event simulation modeling. 

Probabilistic models and decision-making under risk. Topics covered include discrete time Markov chains, a review of the exponential distribution and its properties, the Poisson process, queueing systems, Monte Carlo simulations and decision trees.

Decision making under uncertainty. Topics include decision trees, Monte Carlo simulations, value of information, utility, multi-attribute choice, and applications in operations risk management and design such as quality assurance and supply chains.

Covers optimization and basic methods of linear programming: model formulation,
integer programming, transhipment models, network flow models, and assignment problems

Introduction to data mining and analytics to create business intelligence. Topics include regression analysis, forecasting, optimization and spreadsheet skills.