Teaching machine learning and data literacy to students of logistics using Jupyter Notebooks

First published in
GI-Edition 
Number in series
P-308
Start Page
365
End Page
366
Citation
Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V. (DELFI 2020)
Contribution to Conference
DELFI 2020 – Die 18. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V. 
Publisher Link
https://dl.gi.de/handle/20.500.12116/34190
https://api.ltb.io/show/BMRWS
Scopus ID
2-s2.0-85105448759
Publisher
Gesellschaft für Informatik e.V.
Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks.
Schlagworte
Jupyter Notebooks
Code Literacy
Data Literacy
Machine Learning
Data Science
Logistics
Supply Chain
DDC Class
004: Informatik
370: Erziehung, Schul- und Bildungswesen
Projekt(e)
Maschinelles Lernen in Theorie und Praxis 
More Funding Information
Bundesministerium für Bildung und Forschung (BMBF)
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by-sa/4.0/
Thumbnail Image
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