The ability to understand, analyze, and interpret data for the benefit of businesses has become increasingly important. Therefore, our objective is to equip you with business analytics skills highly demanded in the current job market. The course will focus on building, evaluating, and comparing machine learning, deep learning, and natural language processing (NLP) models as well as understanding how to apply these models to solve real business problems. The class will be hands-on and the emphasis will be placed on the "know-how" aspect - how to apply business analytics to improve business decision making.
This class will also cover quantifying the business value of machine learning models. We’ll talk about how to perform a cost-benefit analysis of predictive models. We will also discuss cost-sensitive classification techniques for incorporating such costs into the model training process. Prior programming skill is not required. However, we will learn how to use Python programming language to work on analytical tasks throughout the semester. We will also work on a diverse set of business cases to promote the understanding of business analytics applications in a variety of business contexts. The assignments and the team projects are all based on real data sets and real cases.