Mechanical & Industrial Engrg 623 - Prescriptive Analytics

Prescriptive analytics is the process of utilizing and analyzing data to make "optimal" decisions. In this course we will build optimization tools for data-driven decision making using Python along with the Gurobi optimizer (available freely for teaching purposes). This course will start with an introduction to both Python and optimization modelling. We will rapidly progress to building large linear programming and mixed integer programming models that are often used for decision making in data-intensive businesses. Projects and case studies will introduce real-world data-rich settings to model and solve through Python-Gurobi. We will discuss how to interpret the solutions that are provided by the software and how to modify the models to accommodate a variety of practical scenarios. By the end of the course, students are expected to have a good grasp of modelling real-world, data-intensive optimization problems, and using Python-Gurobi to solve these problems.

The following is required:

1. The basics of linear algebra
2. The basics of single and multi-variable calculus and optimization
3. The basics of programming (in any language)

Please contact the instructor for any questions about these pre-requisites.