Spring 2024 International Affairs U6503 section R02

Applying Machine Learning

Call Number 14387
Day & Time
Location
F 2:10pm-4:00pm
402 International Affairs Building
Points 0
Grading Mode Ungraded
Approvals Required None
Type LECTURE
Method of Instruction In-Person
Course Description

The spread of information technology has led to the generation of vast amounts of data on human behavior. This course explores ways to use this data to better understand and improve the societies in which we live. The course weaves together methods from machine learning (OLS, LASSO, trees) and social science (theory, reduced form causal inference, structural modeling) to work on real world problems. We will use these problems as a backdrop to weigh the importance of causality, precision, and computational efficiency.

Pre-requisites: Quantitative Analysis II, Microeconomics, and an introductory computer science course (INAF U6006 or equiv). DAQA Registration Priority. Students who have attained mastery of the prerequisite concepts through other means may petition for an exception to the prerequisites using the form: https://forms.gle/na1oDntsce8w5aM8A

Web Site Vergil
Department International and Public Affairs
Enrollment 0 students (1 max) as of 3:04PM Sunday, May 12, 2024
Subject International Affairs
Number U6503
Section R02
Division School of International and Public Affairs
Campus Morningside
Note Recitation
Section key 20241INAF6503UR02