Course # 41430 Section Number 1 Day(s) Tu- Th Time(s) 3:30pm-4:50pm Term Fall 2024 Course Instructor Guillaume Pouliot Syllabus Syllabus 9/18/24 This course explores how modern developments in machine learning, AI and statistical learning may be leveraged in order to improve regression analysis and reduced-form econometrics more generally. For instance, we provide a modern, optimization-conscious treatment of linear regression, quantile regression, instrumental variables, and Fréchet-Hoeffding bounds. Throughout, we make an effort to produce methods that remain valid even when models are --as they always are-- misspecified. To produce such regression methods, we fetch tools and results from fields such as linear programming, optimal transport, numerical linear algebra, deep learning and reinforcement learning. Quarter Title Instructor Day(s) Time(s) Syllabus Fall 2024 Modern Methods for Applied Regression Guillaume Pouliot Tuesday, Thursday 3:30pm-4:50pm Syllabus Fall 2024 Modern Methods for Applied Regression Guillaume Pouliot Tuesday, Thursday 5:00pm-6:20pm Syllabus Recent News More news Student Profile: Zoe Bultman, Persuasive Writing Credential’24 Mon., December 23, 2024 2024 in Review: Our Most Engaging Moments Fri., December 20, 2024 Alumni Profile: Rachel Blume, Policy Analytics Credential’24 Thu., December 19, 2024 Upcoming Events More events Persuasive Writing Credential Mini Class Tue., January 07, 2025 | 7:30 PM The Keller Center 1307 E 60th St Chicago, IL 60637 United States Data and Policy Summer Program (DPSS) Information Session with Alumni Wed., January 08, 2025 | 7:00 AM The Keller Center 1307 E 60th St Chicago, IL 60637 United States Get to Know Harris! A Virtual Information Session Wed., January 08, 2025 | 12:00 PM