Designed to teach students the key concepts of predictive analytics used for deriving value from business data. Students will begin this class with a brief introduction to some of the facets of Artificial Intelligence (AI) e.g., NLP, neural networks, deep learning, and robotics. Focus will then shift to gaining an understanding of the algorithms of machine learning and their application to building predictive models using Python. Topics include cleaning and prepping data, supervised learning, training vs. test data, forecasting numeric values with regression, unsupervised learning, and additional tools to simplify noise from data. Finally, students will revisit applications of deep learning, a subset of machine learning. Prerequisite(s): MSBA 300 and MSBA 320.