Our online graduate certificates allow students to explore the field of Data Analytics and Computational Social Science without committing to a complete master’s degree. Coursework will expose students to data management, research design, and quantitative analysis skills that serve as a foundation for more advanced technical courses offered in the DACSS master’s program.

The 3-course basic certificate, which consists of the core courses below, is intended to develop a foundational understanding of data analytics and computational social sciences. The 5-course advanced certificate extends the basic certificate by providing students with additional training in one or two additional social science methods, such as text analysis, network analysis, survey design and analysis, or machine learning. Students without an existing background in social science are strongly encouraged to take a substantive social science course to better understand the application of the methods.

Course Requirements

DACSS 601: Data Science Fundamentals. This course will introduce and reinforce fundamental data science concepts while providing students with hands-on experience with the DACSS data science/R workflow. Students with no prior experience will have access to efficient guided tutorials to help them get up to speed in R. For students with more programming experience, the flipped classroom approach will allow you to tackle challenging, complex data sets and practice more demanding data science skills in a supportive environment and with feedback geared towards refining coding skills and workflow habits. All students will achieve a solid grounding in general data management, data wrangling skills, and data best practices that are required in all advanced DACSS technical courses. Additionally, you will be able to meet and work with peers in the same cohort; students who will be with you throughout the program.

DACSS 602: Research Design for Social Scientists. This course is a sophisticated and intensive review of a wide range of data collection and analysis methods used in social research (e.g., experiments, interviews, surveys, ethnography, text analysis, single case process tracing.) The course emphasizes how each method can make a valid contribution to our understanding of social, political, and economic life. Students will learn how to design and interpret social scientific studies using different methods of data collection and analysis that are increasingly likely to be encountered in business and policy settings (prior exposure to a research design or research methods course at the college-level is helpful, but not required).

DACSS 603: Introduction to Quantitative Analysis. This course will provide students with an introduction to quantitative analysis in the social sciences, often referred to as econometrics or statistical analysis. The course will introduce students to statistical techniques including ordinary least squares (OLS), limited dependent variable analysis, and other quantitative analysis models (requires DACSS 601 or prior experience using R).

For the advanced certificate, two additional courses are required:

Technical Electives. Choose one or two technical courses such as survey research, text as data, advanced quantitative methods in anthropology, geospatial analysis, modeling emergence and social simulation, experimental economics, panel data econometrics, social and political network analysis, and applied time series econometrics. Example technical courses can be found here.

Substantive Electives. Choose no more than one course featuring a substantive social science topic. Any graduate courses offered by a department in the College of Social and Behavioral Sciences (SBS) can be used to fulfill this requirement with the consent of the instructor and approval of the DACSS Program Director. Example substantive courses can be found here.