A Course on Advanced Software Tools for Operations Research and Analytics

Abstract

It is increasingly important for researchers and practitioners to be familiar with methods and software tools for analyzing large data sets, formulating and solving large-scale mathematical optimization models, and sharing solutions using interactive media. Unfortunately, advanced software tools are seldom included in curricula of graduate-level operations research (OR) and analytics programs. We describe a course consisting of eight three-hour modules intended to introduce master’s and Ph.D. students to advanced software tools for OR and analytics: machine learning in R, data wrangling, visualization, big data, algebraic modeling with JuMP, high-performance and distributed computing, Internet and databases, and advanced mixed integer linear programming (MILP) techniques. For each module, we outline content, provide course materials, summarize student feedback, and share lessons learned from two iterations of the course. Student feedback was very positive, and all students reported that the course equipped them with software skills useful for their own research. We believe our course materials could serve as a template for the development of effective OR and analytics software tools courses and discuss how they could be adapted to other educational settings.