This course offers students an introduction to the basic concepts and applications of predictive analytics, which is a broad domain of data analytical practice focused on developing forward-looking statistical estimates. The course begins with an overview of predictive and prescriptive analytics, followed by immersion in statistical prediction-related multivariate statistical concepts, including an in-depth discussion of commonly used types of multivariate predictive models, all focused on strengthening students’ comprehension of core statistical notions, including variable types, statistical learning, statistical regression and classification, non-linear modeling, and tree-based estimation. The second part of the course focuses on hands-on applications of model fitting and evaluation using programming applications in R or Python. Credits: 4