Course # 41430 Section Number 2 Day(s) Tu- Th Time(s) 5:00pm-6:20pm Term Fall 2024 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 Tuesday, Thursday 3:30pm-4:50pm Syllabus Fall 2024 Modern Methods for Applied Regression Tuesday, Thursday 5:00pm-6:20pm Syllabus Recent News More news Provost Katherine Baicker Appointed Emmett Dedmon Distinguished Service Professor Thu., July 03, 2025 Alumni Profile: Daisuke Kageyama, MPP'23 Thu., June 26, 2025 Inside the Machinery of Misinformation: Konstantin Sonin Explores How Authoritarian Regimes Manipulate Minds Wed., June 25, 2025 Upcoming Events More events Harris Summer Mixer in Bogotá Sat., July 05, 2025 | 8:00 PM Andrés DC Cl. 82 #12 -21 Bogotá, DC, 110221 Colombia Harris Summer Campus Visit Mon., July 07, 2025 | 10:00 AM Harris School of Public Policy 1307 E 60th St Chicago, IL 60637 United States Get to Know Harris! A Virtual Information Session Wed., July 09, 2025 | 8:30 AM