In this course, the student will learn to identify, evaluate, and capture business analytic opportunities that create value for an organization. Theoretical data analytics methods, as well as case studies on successful analytics applications, will be covered. Basic descriptive analytics methods are reviewed along with a quick introduction to using 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.

This talk provides an overview of financial markets and its players, followed by an introduction to algorithmic trading systems and how they work. Special focus will be given to the skills most demanded in the industry.

Especially recommended for engineers, computer scientists and mathematicians, this workshop provides a solid foundation in the principles of finance as they apply in the real world. The participants will gain some of the necessary quantitative, computing, and programming skills required to fulfill a career in hedge funds and investment banks.