Machine Learning for Economists
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Overview
Subject area
ECON
Catalog Number
81230
Course Title
Machine Learning for Economists
Department(s)
Description
Recent developments in artificial intelligence and constantly growing computationalpower provide economists with unprecedented capacities for the data analysis. This course provides a broad overview of numerical methods at the intersection ofmathematics, statistics and computer science that constitute the workhorse of themodern data analytics. In particular, the course provides an introduction to machinelearning, deep learning, reinforcement learning, parallel computing and big datamethods, as well as data manipulation, visualization, presentation and interpretation techniques. The studied applications are not limited to conventional econometric regressions models but contain some prominent examples from computer science,such as recognition of handwritten numbers. The course also introduces students to programming in Python with the emphasis on economic applications.
Typically Offered
Offer as needed
Academic Career
Graduate School Graduate
Liberal Arts
Yes
Credits
Minimum Units
3
Maximum Units
3
Academic Progress Units
3
Repeat For Credit
No
Components
Name
Lecture
Hours
3
Requisites
030895