NEW! Join us for the 2022 DS4CG Celebration Lunch and Poster Session: September 27, 11-1 ET. Learn more and RSVP.
Data Science for the Common Good (DS4CG) is a summer program that trains aspiring data scientists to work on real-world problems that benefit the common good. Our teams of computer science Master's students collaborate with nonprofit organizations and government agencies working in public health, education, health and wellness, environmental conservation, and more.
Why Data Science for the Common Good?
Non-profit and public-sector organizations acquire, store, and use data in ever-increasing volumes and varieties, but they typically lack the in-house technical expertise needed to develop improved ways to use their existing data holdings, enhance their data collection and analysis methods, or create entirely new applications of their data.
CDS is leading efforts to provide education and research pathways for aspiring data scientists to apply their knowledge and skills to benefit society. Students do not have many opportunities to be exposed to the vital and compelling work of community non-profits and public-sector agencies, yet are increasingly motivated by the desire to direct their talents towards making the world a better place.
DS4CG harnesses growing student interest in social-good causes and connects it to partner organizations that stand to benefit from the students’ growing data science expertise.
How DS4CG Works
DS4CG is a summer program conducted over 12 weeks from May to August. Participating students, called DS4CG fellows, perform their work and are supervised by CDS faculty and staff in paid internships comparable to private-sector industry internships. No fee is charged to the partner organizations; however, to fully realize the benefits of participation, partners are expected to allocate staff time to engage regularly with our student teams. In addition, fellows are supported by volunteer professional data science advisors drawn from CDS’s pool of corporate affiliates.
DS4CG serves organizations that lack staff capacity to exploit state-of-the-art analysis and modeling of their business data. Ideal DS4CG projects incorporate analysis and integration of very large volumes of data, with different types and formats. DS4CG fellows compile, organize and clean these datasets, mathematically explore their statistical properties, build predictive models and forecasts, and visualize the results. Project deliverables can include actionable data-driven insights, presentations, reports, and proof-of-concept software tools.
Thank you to our program sponsors
