Predictive Analytics

Catalog description

The course provides the application of foundational topics for supervised learning algorithms such as Multiple Linear Regression, Logistics Regression, Nearest Neighbors, Decision and Regression Trees, Discriminant Analysis, Neural Networks, and Ensemble Methods. It first builds a sound understanding of data preparation, exploration, and reduction methods. This course covers prediction as well as classification processes. The emphasis is on learning the application of different machine learning techniques for decision-making situations across business domains rather than mastering the techniques' mathematical and computational foundations. Prerequisite Course(s): Prerequisites: QANT 501 or permission of the chair