Machine Learning for Social Scientists

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Course Description

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.

Cross Listed Courses

Grading Basis

ROP - Letter or Credit/No Credit

Min

5

Max

5

Course Repeatable for Degree Credit?

No

Course Component

Discussion

Enrollment Optional?

Yes

Course Component

Lecture

Enrollment Optional?

No

This course has been approved for the following WAYS

Applied Quantitative Reasoning (AQR)

Does this course satisfy the University Language Requirement?

No

Programs

POLISCI150B is a completion requirement for: