This course is an introduction to machine learning and big data for use in economic analysis. Machine learning employs techniques for analyzing large data sets with an emphasis on making predictions. The econometric methods covered in Economics 2222A/B and Economics 2223A/B are extended to common machine learning methods such as random forest and artificial neural networks.  

Antirequisite(s): Data Science 3000A/B, the former Computer Science 4414A/B, and the former Software Engineering 4460A.

Prerequisite(s): Economics 2223A/B.

Extra Information: 1 lecture hour, 2 laboratory hours.