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:
 A total of three courses from the list below, with the following requirements:
 At least one of which must not count towards their home department Ph.D. requirements.
 At least one of the selected classes must be from the subset of “advanced data” courses.
 Only one total undergraduate upper division course from the list below is permitted towards satisfaction of the specialization.
 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 subdisciplines of computational social science.
 Appointment to the dissertation committee of at least one CSS affiliated faculty member not affiliated with the student’s home department.
 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