Francine Berman
Rob Rutenbar
Brent Hailpern
Susan Davidson
Deborah Estrin
Abstract
Data science promises new insights, helping transform information into knowledge that can drive science and industry.
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Cross Ref
- Berman, F. (co-chair), Rutenbar, R. (co-chair), Christensen, H., Davidson, S., Estrin, D., Franklin, M., Hailpern, B., Martonosi, M., Raghavan, P., Stodden, V., and Szalay, A. Realizing the Potential of Data Science: Final Report from the National Science Foundation Computer and Information Science and Engineering Advisory Committee Data Science Working Group. National Science Foundation Computer and Information Science and Engineering Advisory Committee Report, Dec. 2016; https://www.nsf.gov/cise/ac-data-science-report/CISEACDataScienceReport1.19.17.pdfGoogle Scholar
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- University of California, Berkeley. Data Science Education Program; http://data.berkeley.edu/data-science-education-programGoogle Scholar
- University of Chicago. Master of Science in Computational Analysis & Public Policy; https://capp.uchicago.edu/Google Scholar
- University of Illinois, Urbana-Champaign, CS@ILLINOIS. Master of Computer Science in Data Science, Data Science Track; http://www.cs.uiuc.edu/academics/graduate/professional-mcs-program/mcs-data-science-trackGoogle Scholar
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- Waldrop, M.M. The chips are down for Moore's Law. Nature 530, 7589 (Feb. 11, 2016), 144--146.Google ScholarCross Ref
Index Terms
- Realizing the potential of data science
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