Computational Social Science Certificate

The faculty supporting this certificate unite for a common goal: to create an environment for social science Ph.D. students to acquire theoretical knowledge and mastery of computational skills necessary for analyzing large and complex data.

Learning Outcomes:

A.  Students need mastery of a computer language which enables them to utilize the computational tools available.  This would include Python, R, or some other recognized computer language appropriate for CSS research.  They must demonstrate that they can use these tools to execute their research. 

B. Students need to develop and demonstrate proficiency in at least one method of computationally-intensive data collection, extraction, or analysis.  This would include mastery of machine learning, computational linguistics, network analysis, visualization data management, web scraping, agent based modeling, and advanced statistical modeling among other techniques. 

C. Students need to understand CSS as a broad epistemology or approach to establishing credible knowledge, its history, and the ethical issues associated with CSS.  They also need to be able to explain to non-experts the computational approaches they have learned and used in their research. 

The achievement of these outcomes will be assessed by students’ performance in the required course and three electives they must complete for the certificate.