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Introductory data science across disciplines, using Python, case studies, and industry consulting projects
Teaching Statistics ( IF 1.2 ) Pub Date : 2020-10-26 , DOI: 10.1111/test.12243
Jana Lasser 1, 2, 3 , Debsankha Manik 2 , Alexander Silbersdorff 3, 4 , Benjamin Säfken 3, 4 , Thomas Kneib 3, 4
Affiliation  

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived insights. On the basis of recent experiences at the University of Ttingen, Germany, we present a new approach to teach the relevant data science skills as an introductory service course at the university or advanced college level. We describe the outline of a complete course that relies on case studies and project work built around contemporary data sets, including openly available online teaching resources.

中文翻译:

跨学科的介绍性数据科学,使用 Python、案例研究和行业咨询项目

数据及其应用在快速数字化的世界中越来越普遍,因此,不同学科的学生面临着越来越多的技能需求,以应对学术界和企业日益增长的从数据中收集、管理、评估、应用和提取知识并批判性反思的需求。基于衍生的见解。在德国 Ttingen 大学最近的经验的基础上,我们提出了一种新的方法来教授相关的数据科学技能,作为大学或高级学院水平的介绍性服务课程。我们描述了一个完整课程的大纲,该课程依赖于围绕当代数据集构建的案例研究和项目工作,包括公开可用的在线教学资源。
更新日期:2020-10-26
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