Curriculum Guidelines for Undergraduate Programs in Data Science

Рекомендации по разработке учебных планов бакалаврских программ по науке о данных
Richard D. De Veaux, Mahesh Agarwal, Maia Averett, Benjamin S. Baumer, Andrew Bray, Thomas Bressoud, Lance Bryant, Lei Z. Cheng, Amanda Francis, Robert Gould, Albert Y. Kim, Matt Kretchmar, Qin Lu, Ann Moskol, Deborah Nolan, Roberto Pelayo, Sean Raleigh, Ricky J. Sethi, Mutiara Sondjaja, Neelesh Tiruviluamala, Paul X. Uhlig, Talitha Washington, Curtis L. Wesley, David White, Ye Ping
2017-01-09

curriculum guidelinesdata science majormathematicsstatisticsundergraduate data science
The Park City Math Institute 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in data science. The group consisted of 25 undergraduate faculty from a variety of institutions in the United States, primarily from the disciplines of mathematics, statistics, and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in data science.
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A Park City Math Institute working group developed curriculum guidelines for undergraduate data science programs.
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The guidelines are intended to structure the development or revision of undergraduate data science majors.
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The guidelines were authored by 25 faculty members from diverse U.S. institutions, primarily representing mathematics, statistics, and computer science.

undergraduate data science programs

curriculum guidelines and structural recommendations for planning or revising undergraduate data science majors

Publication Details
Publication Date
2017-01-09
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Authors
Richard D. De Veaux
Mahesh Agarwal
Maia Averett
Benjamin S. Baumer
Andrew Bray
Thomas Bressoud
Lance Bryant
Lei Z. Cheng
Amanda Francis
Robert Gould
Albert Y. Kim
Matt Kretchmar
Qin Lu
Ann Moskol
Deborah Nolan
Roberto Pelayo
Sean Raleigh
Ricky J. Sethi
Mutiara Sondjaja
Neelesh Tiruviluamala
Paul X. Uhlig
Talitha Washington
Curtis L. Wesley
David White
Ye Ping
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