This master course demystifies neural networks by building them from scratch and linking the underlying techniques to practical business use cases. It also examines how to build and evaluate AI systems that are not only accurate but also interpretableandaccountable. Students will learn not only how to use AI tools, but how they work, and the practical tools to explain model predictions, manage risk, and support data-driven decision-making.

This Master Course will be taught by:
David Wanik
Academic Director, Business Data Analytics 
Associate Professor In-Residence
Operations and Information Management Department