ECON 224Economic Applications of Machine Learning
Introduces machine learning methods and their application to econometrics and applied economics. Covers the traditional use of machine learning for solving prediction problems and recent research applying the methods to causal inference and counterfactual prediction. Students learn the basic theory justifying the use of these methods and gain experience implementing them in R using economic data. Through class discussions, students study examples of applied economic research utilizing machine learning methods.
Prerequisite(s): ECON 211A, ECON 211B and ECON 211C, or ECON 216 and ECON 217. Recommended prerequisites: M.S. QEFN students should have A’s in the econometrics sequence and be comfortable with linear algebra. Experience with R, MATLAB, Python, or related programming language is very strongly recommended, as the course will not teach basic programming.
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When it runs
Spring 2026Open Spring 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 11:40am–1:15pm | J Baskin Engr 169 | M. Leung | Open 9/15 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Michael Leung | 5.0 / 5 | 3.0 / 5 | 100% | 5 |
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