Social Sciences

Education and Training

Successful adoption of data science will require several linked efforts. Domain scientists need training in the foundations of data science, including programming, statistics, and reproducible computational science, while methodological scientists need training to work productively in domain areas. This working group addresses these needs through a combination of activities, including workshops and bootcamps.

Career Paths and Alternative Metrics

The current system for career advancement in research universities, which is heavily weighted toward publication, often does not align with what makes a modern data scientist successful. This working group aims at identifying and promoting alternative metrics and career paths that lead to growth and advancement opportunities for scientists who do not fit the typical academic mold but are critical to its success.

Data Science Lecture Series: Maximizing Human Potential Using Machine Learning-Driven Applications

The Berkeley Institute for Data Science: A Place for People Like Us | SciPy 2014 | Fernando Perez

Data Science at Berkeley

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