Spring 2023
POLSCI 132B 001 - LEC 001
Machine Learning for Social Scientists
Kirk C Bansak
Class #:32660
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Charles & Louise Travers Dept of Political Science
Current Enrollment
Total Open Seats:
0
Enrolled: 54
Waitlisted: 0
Capacity: 54
Waitlist Max: 0
Open Reserved Seats:0
Hours & Workload
3 hours of instructor presentation of course materials per week, 8 hours of outside work hours per week, and 1 hours of the exchange of opinions or questions on course material per week.
Final Exam
THU, MAY 11TH
03:00 pm - 06:00 pm
Anthro/Art Practice Bldg 160
Dwinelle 104
Other classes by Kirk C Bansak
Course Catalog Description
Social scientists and policymakers increasingly use large quantities of data to make
decisions and test theories. For example, political campaigns use surveys, marketing
data, and previous voting history to optimally target get out the vote drives.
Governments deploy predictive algorithms in an attempt to optimize public policy
processes and decisions. And political scientists use massive new data sets to measure
the extent of partisan polarization in Congress, the sources and consequences of media
bias, and the prevalence of discrimination in the workplace. Each of these examples,
and many others, make use of statistical and algorithmic tools that distill large quantities
of raw data into useful quantities of interest.
Class Notes
Students must have taken PS 3 or Data 8 (or have equivalent coursework).
Rules & Requirements
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials