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Introductory data science across disciplines, using Python, case studies, and industry consulting projects.

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Title: Introductory data science across disciplines, using Python, case studies, and industry consulting projects.
Authors: Lasser, Jana1,2,3 (AUTHOR) lasser@csh.ac.at, Manik, Debsankha2 (AUTHOR), Silbersdorff, Alexander3,4 (AUTHOR), Säfken, Benjamin3,4 (AUTHOR), Kneib, Thomas3,4 (AUTHOR)
Source: Teaching Statistics. Jul2021 Supplement S1, Vol. 43, pS190-S200. 11p.
Subject Terms: *Case studies, *Upper level courses (Education), *Universities & colleges, Data science
Geographic Terms: Germany
Abstract: 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. [ABSTRACT FROM AUTHOR]
Copyright of Teaching Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Teaching Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jul2021 Supplement S1
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