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Introduction to Computational Social Science

MS&E
231
Instructors
Ugander, J. (PI)
Fischer, M. (TA)
Zanotti, G. (TA)
Section Number
1
With a vast amount of data now collected on our online and offline actions -- from what we buy, to where we travel, to who we interact with -- we have an unprecedented opportunity to study complex social systems. This opportunity, however, comes with scientific, engineering, and ethical challenges. In this hands-on course, we develop ideas from computer science and statistics to address problems in sociology, economics, political science, and beyond. We cover techniques for collecting and parsing data, methods for large-scale machine learning, and principles for effectively communicating results. To see how these techniques are applied in practice, we discuss recent research findings in a variety of areas. Prerequisites: introductory course in applied statistics, and experience coding in R, Python, or another high-level language.
Grading
Letter or Credit/No Credit
Units
3
Academic Career
Graduate
Course Tags
Science and Technology Policy - Gateway
Computational Policy - Electives
Computational Policy Analysis
Academic Year
Quarter
Autumn
Section Days
Tuesday Thursday
Start Time
9:00 AM
End Time
10:20 AM
Location
STLC 115