“In just a few years, AI has grown from a niche, specialized discipline to a must-have for organizations around the world. But not all AI is appropriate for every company. This program will provide executives with an understanding of what can and is being done in a range of industries to help them bring these technologies to the forefront in their work.”
Assaf Zeevi and Daniel GuettaThe program's Faculty Directors
Day 1 will feature an AI crash course for executives. You'll get introduced to the fundamental concepts that underlie modern AI and analytics techniques and touch on the technologies that enable these efforts. This introduction will set you up to understand the examples in the remainder of the class and allow you to start thinking about AI applications in your own organization.
Associate Professor of Professional Practice
Columbia Business School
Daniel Guetta is an associate professor of Professional Practice at Columbia Business School and Director of the Business Analytics Initiative at the Columbia Business School and Columbia Engineering. His research focuses on the ways companies can harness the power of data and analytics to drive value. He teaches classes in business analytics, including data science, pricing, supply chain management, and technical tools such as Python and cloud computing.
Guetta has authored award-winning case studies in the area with a number of companies and co-authored Python for MBAs. He was the 2020 recipient of the Singhvi Prize for Scholarship in the classroom. Prior to joining the faculty at Columbia Business School, he was a data scientist and engagement manager at Palantir Technologies, where he worked with clients around the world in fields ranging from finance to pharmaceuticals to help them solve their hardest problems using data. He completed his undergraduate studies in physics and mathematics at Cambridge and MIT and holds a PhD in Operations Research from the Columbia Business School.
Kravis Professor of Business
Columbia Business School
Assaf Zeevi is a Kravis Professor of Business at Columbia Business School. His research and teaching interests lie at the intersection of operations research, data science, and AI. He has been developing theory and algorithms for machine learning and overseeing their translation to industry implementations. His work has found applications in online retail, healthcare analytics, dynamic pricing, recommender systems, and online marketplaces. He is a member of several scientific advisory boards for startup companies in the high technology sector. Assaf received his BSc and MSc (Cum Laude) from the Technion in Israel and his PhD from Stanford University in 2001. He has held visiting positions at Stanford University, the Technion, and Tel Aviv University.
Sign up for program updates and content relevant to today's business leaders from Columbia Business School Executive Education.