We put together this manual for fellows in the Data Science for Social Good program at the University of Chicago. We are making it public to provide insight into the program to anyone interested in doing data science for social good, including potential fellows, mentors, and project partners, as well as those interested in funding or replicating such a program.
- Before You Arrive: Prerequisites and Software Setup
- What to Expect from the Fellowship: Code of Conduct, Culture and Communications and Summer Overview
Welcome to the Data Science for Social Good (DSSG) Fellowship program! We hope your experience this summer will help you grow your skills as a data scientist and learn how to apply those skills to solve real-world problems with social impact. This manual outlines our goals in running this fellowship program, our hopes for your experience, and our expectations of the participants. We’ve also outlined how the summer is typically structured and what you can expect from us.
This manual was created collaboratively at the Center for Data Science and Public Policy at the University of Chicago, with lots of help from various sources including those listed below. Contributors include Bridgit Donnelly, Matt Gee, Rayid Ghani, Maya Grever, Lauren Haynes, Jen Helsby, Lindsay Knight, Benedict Kuester, Joe Walsh, and Jane Zanzig.
This manual is licensed under the Creative Commons Zero license.
Parts of this manual are based on several other policies, including
- The Recurse Center User's Manual
- AlterConf Code of Conduct
- Django Community Code of Conduct
- SRCCON Code of Conduct
- Citizen Code of Conduct