A Data Science Course for Undergraduates: Thinking With Data
A Data Science Course for Undergraduates: Thinking With Data
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DOI：
10.1080/00031305.2015.1081105
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发表时间：
2015-10-02
影响因子：
1.8
通讯作者：
Baumer, Ben
中科院分区：
文献类型：
--
作者：
Baumer, Ben
数据科学是一个新兴的跨学科领域，它结合了数学，统计学，计算机科学和特定应用领域的知识，目的是从许多环境中日益复杂的数据中提取有意义的信息。这些数据往往是非传统的，从某种意义上说，它们通常是实时的，大型的，复杂的和/或混乱的。本科阶段的统计学第一门课程通常向学生介绍各种技术来分析小，整洁和干净的数据集。然而，无论他们是否接受更正式的统计学培训，这些学生中的许多人最终都会处理相当复杂的数据，并且需要掌握统计计算技术。更重要的是，这些学生需要一个框架来结构化地思考数据。我们描述了一个文科环境中的本科课程，为学生提供应用数据科学所需的工具。该课程强调现代，实用和有用的技能，涵盖整个数据分析范围，从提出有趣的问题到获取，管理，操作，处理，查询，分析和可视化数据，以及以书面，图形和口头形式传达结果。本文的补充材料可在网上查阅。[2014年6月收到。2015年7月修订）。
Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be nontraditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students to a variety of techniques to analyze small, neat, and clean datasets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that are considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms. Supplementary materials for this article are available online.[Received June 2014. Revised July 2015.]