Curriculum Guidelines for Undergraduate Programs in Data Science

R. D. Veaux, Mahesh Agarwal, Maia Averett, Benjamin S. Baumer, Andrew Bray, T. Bressoud, Lance Bryant, Lei Cheng, Amanda Francis, R. Gould, Albert Y. Kim, Matt Kretchmar, Qin Lu, Ann Moskol, D. Nolan, Roberto Pelayo, Sean Raleigh, Ricky J. Sethi, Mutiara Sondjaja, Neelesh Tiruviluamala, P. Uhlig, Talitha M. Washington, Curtis L. Wesley, David L. White, Ping Ye
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引用次数: 165

Abstract

The Park City Math Institute (PCMI) 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 U.S., 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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数据科学本科课程指南
帕克城数学学院(PCMI) 2016年夏季本科教师课程旨在为数据科学本科课程编写指导方针。该小组由来自美国不同院校的25名本科教师组成,主要来自数学、统计学和计算机科学等学科。这些指导方针旨在为院校规划或修订数据科学专业提供一些框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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