ECON 81230
Machine Learning for Econmists · 3 credits · Spring 2027
Requirements
Class is open to either ECON or BUS Majors
About this course
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.
No sections have been posted for this course in this term yet.