Introductory data science across disciplines, using Python, case studies, and industry consulting projects
2021-06-25 | journal article; research paper. A publication with affiliation to the University of Göttingen.
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- Authors
- Lasser, Jana; Manik, Debsankha; Silbersdorff, Alexander ; Säfken, Benjamin; Kneib, Thomas
- Abstract
- 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.
- Issue Date
- 25-June-2021
- Journal
- Teaching Statistics
- Organization
- Max-Planck-Institut für Dynamik und Selbstorganisation ; Zentrum für Statistik ; Campus-Institut Data Science
- Language
- English
- Sponsor
- Stifterverband http://dx.doi.org/10.13039/501100008384
WOA Institution: GEORG‐AUGUST‐UNIVERSITAET GOTTINGEN Blended DEAL: ProjektDEAL