Data Analytics for Operations Research and Financial Engineering

Students will learn to identify, evaluate and capture analytic opportunities that create value for an organization. Basic descriptive analytics methods are reviewed utilizing specialized software (e.g. R) in analyzing large data sets. Predictive analytics techniques including clustering, classification and regression are covered in detail. Prescriptive analytics applications on utilization simulation and optimization over large data to improve business decisions are presented. Case studies emphasize financial applications, such as portfolio management and automated trading.