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Curriculum

Students in the graduate specialization in Computational Social Science are expected to complete all Ph.D. requirements of their home department.  

To satisfy the requirements of the specialization, students will also have to complete:

  1. A total of three courses from the list below, with the following requirements:
    1. At least one of which must not count towards their home department Ph.D. requirements.
    2. At least one of the selected classes must be from the subset of “advanced data” courses.
    3. Only one total undergraduate upper division course from the list below is permitted towards satisfaction of the specialization.  
  2. Three quarters of CSS 209. Computational Social Science Research Seminar, a weekly seminar series planned to be offered quarterly in fall, winter, and spring beginning in Fall 2022. These formal talks will provide one of several opportunities for serendipitous interaction and deeper discussion across the various sub-disciplines of computational social science.  
  3. Appointment to the dissertation committee of at least one CSS affiliated faculty member not affiliated with the student’s home department.
  4. Satisfactory completion of a dissertation including a technical and/or computational social science component.

Electives

Course Number

Course Name

Prerequisites

Advanced Data Category?

COGS 202

Cognitive Science Foundations: Computational Modeling of Cognition

None

COGS 225

Visual Computing

None

COGS 283

Big Data Visual Processing

None

X

ECON 109

Game Theory

ECON 100C or MATH31 CH or MATH 109 or CSE 20 and MATH 20C

ECON 120A

Econometrics A

ECON 1; and MATH 10C or MATH 20C or MATH 31BH

ECON 120B

Econometrics B

ECON 120A or ECE 109 or MAE 108 or MATH 180A or MATH 183 or MATH 186

ECON 120C

Econometrics C

ECON 120B and MATH 181B

ECON 125

Demographic analysis and forecasting

ECON 120B

ECON 200A

Microeconomics

None

ECON 200B

Microeconomics

ECON 200A

ECON 200C

Microeconomics

ECON 200B

ECON 206

Decisions

ECON 200ABC

ECON 208

Games and Information

ECON 200ABC

ECON 210A

Macroeconomics

None

ECON 210B

Macroeconomics

ECON 210A

ECON 210C

Macroeconomics

ECON 210B

ECON 220C

Econometrics

ECON 220B

X

ECON 220D

Econometrics

ECON 220C

X

ECON 220E

Econometrics

ECON 220D

X

ECON 227

Nonparametric and Semiparametric Models

ECON 220ABCDE

X

ECON 263

Modeling Behavioral Economics

ECON 200ABC

LIGN 167

Deep Learning for Natural Language Understanding

MATH 10C or MATH 20C or MATH 31BH

POLI 176

Text as Data

POLI/ECON 5D or POLI 30D or POLI 170A or POLI 171 or POLI 172

POLI 204C

Game Theory I

None

POLI 205

Game Theory II

POLI 247B

Formal Models in International Relations

None

POLI 272

Bayesian Methods

None

X

POLI 273

Causal Inference

None

X

POLI 274

Text as Data

None

X

POLI 279

Special Topics in Methodology: Networks

X

POLI 287*

Multidisciplinary Methods in Political Science: Social Networks

POLI 204A, 204B, 204C

X

POLI 288

Multidisciplinary Methods in Political Science: Computational Social Science

POLI 204A, 204B, 204C

X

PSYC 201B

Quantitative methods

None

X

PSYC 211

Computational models of mind

None

SOCG 209

Social Networks

None

X

SOCG 211

Introduction to Computational Social Science/Text Classification

None

X

SOCG 290

Theories/Practice of Big Data for Social Scientists

None

*Limited to students whose home department is Political Science