Summer Institutes in Computational Social Science (SICSS)

The Summer Institutes in Computational Social Science (SICSS) were created to provide free training to the next generation of researchers at the intersection of social science and data science— and to incubate cutting-edge research across disciplinary boundaries. We provide state-of-the art training in a range of different areas in computational social science from ethics to text analysis and mass collaboration. These lectures assume a basic, working knowledge of the R language.

Data Carpentry for Social Sciences

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

Data Carpentry for Social Sciences

This workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.