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Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks

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dc.contributor.authorKastner, Marvin
dc.contributor.authorFranzkeit, Janna
dc.contributor.authorLainé, Anna
dc.contributor.editorZender, Raphael
dc.contributor.editorIfenthaler, Dirk
dc.contributor.editorLeonhardt, Thiemo
dc.contributor.editorSchumacher, Clara
dc.date.accessioned2020-09-08T09:46:28Z
dc.date.available2020-09-08T09:46:28Z
dc.date.issued2020
dc.description.abstractTeaching 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.en
dc.identifier.isbn978-3-88579-702-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34190
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDELFI 2020 – Die 18. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V.
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-308
dc.subjectJupyter Notebooks
dc.subjectCode Literacy
dc.subjectData Literacy
dc.subjectMachine Learning
dc.subjectData Science
dc.subjectLogistics
dc.subjectSupply Chain
dc.titleTeaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooksen
dc.typeText/Conference Paper
gi.citation.endPage366
gi.citation.publisherPlaceBonn
gi.citation.startPage365
gi.conference.date14.-18. September 2020
gi.conference.locationOnline

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P308 - DELFI 2020 - Die 18. Fachtagung Bildungstechnologien
DELFI 2020