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:
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.
4. All three elective courses must be taken for a letter grade.
Three quarters of CSS 209. Computational Social Science Research Seminar, a weekly seminar series to be offered quarterly in fall, winter, and spring. These formal talks will provide one of several opportunities for serendipitous interaction and deeper discussion across the various sub-disciplines 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

**If you have identified a faculty member from outside of your department who is not affiliated with CSS but whom you believe would be a valuable addition to your committee (even if just in using similar methodology regularly), please reach out to us to discuss the potential affiliation of this faculty member with the CSS program.