Data Science and AI Modeling for Executives II

Catalog description

This graduate-level course, part of a 3 part sequence, is designed for students interested in learning the foundations of machine learning. The focus will be on applying these techniques to applications in specific policy related scenarios. We will cover the intuition of the theoretical underpinnings, but the focus here is on using supervised and unsupervised learning tools. We will cover topics ranging from predictions and classification to clustering. We will use Python and learn to utilize Jupyter Notebooks. Using these tools, students will learn the underpinnings of each method so that they can choose the most appropriate for particular applications.