Objective of Machine Learning (ML) and AI course in health is to provide graduate students/professionals with formal training in predictive models, ML, neural networks, and dimensional reduction, and skills necessary to apply statistical/machine learning methods in precision and population health including electronic medical records, surveillance and policy. Topics include popular multivariate statistical, and machine learning methods to solve complex or big data problems. This is a context-based course with several hands-on practice examples. Information to compare black box ML models with more transparent statistical methods will be shared. Python will be used as the primary programming language. R usage is also permitted. All of US database will be introduced. Course content can be applied in biotech, business, cancer, cardiovascular, cognitive sciences/psychometry, environmental sciences, genetics, health policy, and pharmacy.

*Please note: this session will take place in Central Time (Chicago Time)*