Machine Learning for Social Scientists (POLISCI 355B)

POLISCI
150B
Instructors
Peters, A. (TA)
Bonica, A. (PI)
Yorgason, C. (TA)
Section Number
1
Machine learning - the use of algorithms to classify, predict, sort, learn and discover from data - has exploded in use across academic fields, industry, government, and the non-profit sector. This course provides an introduction to machine learning for social scientists. We will introduce state of the art machine learning tools, show how to use those tools in the programming language R, and demonstrate why a social science focus is essential to effectively apply machine learning techniques in social, political, and policy contexts. Applications of the methods will include forecasting social phenomena, evaluating the use of algorithms in public policy, and the analysis of social media and text data. Prerequisite: POLISCI 150A/355A.
Grading
Letter or Credit/No Credit
Requirements
WAY-AQR
Units
5
Undergraduate
Course Tags
Computational Policy - Electives
Computational Policy Analysis
Academic Year
Quarter
Winter
Section Days
Tuesday Thursday
Start Time
11:30 AM
End Time
1:00 PM
Location
160-124