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Courses - Summer 2026
ECON
Economics Department Site
Open Seats as of
03/18/2026 at 10:30 PM
ECON685
Economic Applications of Machine Learning with Python
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: ECON641; and must have completed or be concurrently enrolled in ECON645.
Restriction: Must be enrolled in a version of the MS in Applied Economics Program (ECAM, ECAO, ECAE); or permission of the program director.
Offers a comprehensive examination of the concepts and techniques used in machine learning using Python, with specific emphasis on their applications in economics. Students will explore linear and non-linear regression and classification methods, k-nearest neighbors, tree-based approaches, support vector machines, neural networks, regularization, and dimensionality reduction methods. The course also offers a wide range of assessments, model evaluation, and model selection methods.