Training

Computational Social Science Training Program (CSSTP)

The UC Berkeley Computational Social Science Training Program (CSSTP) trains predoctoral students representing a variety of degree programs and expertise areas in the social sciences, including demography, public health, public policy, social epidemiology, social welfare, and sociology.

Launched in 2020 with a five-year, $1.2 million grant from the National Institutes of Health (NIH) Office of Behavioral and Social...

Computational Research for Equity in the Legal System Training Program (CRELS)

About

The UC Berkeley Computational Research for Equity in the Legal System Training Program (CRELS) trains doctoral students representing a variety of degree programs and expertise areas in the social sciences, computer science and statistics.

Launched in 2023 with a $3-million grant from the National Science Foundation (NSF), this five-year multidisciplinary training program in data science and social science disciplines fosters a new computational social science research community and leads the integration of research on the social...

Machine Learning and Science Forum

The BIDS Machine Learning and Science Forum (originally the Berkeley Statistics and Machine Learning Forum) was launched in Spring 2018 and currently meets biweekly (during the spring and fall semesters) to discuss current applications across a wide variety of research domains in the physical sciences and beyond. These active sessions bring together domain scientists, statisticians, and computer scientists who are either developing state-of-the-art methods or are interested in applying these methods in their research. This Forum is hosted by BIDS Faculty Affiliate...

Data Science By Design (DSxD)

Data Science By Design (DSxD) is a community of practice to curate ideas about data narratives, innovative communication approaches and aesthetic visual design principles. This project aims to conscientiously develop the future of data science with diversity, inclusion, and open education as guiding principles that incorporate transparent research practices and accessible training. Our events and resources will empower and support attendees to produce visual content that effectively and artfully communicates the practice of data science research in the form of how-to...