Kastner, MarvinMarvinKastnerFranzkeit, JannaJannaFranzkeitLainé, AnnaAnnaLainé2020-10-012020-10-012020-09Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V. (DELFI 2020)http://hdl.handle.net/11420/7423Teaching 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.enhttps://creativecommons.org/licenses/by-sa/4.0/Jupyter NotebooksCode LiteracyData LiteracyMachine LearningData ScienceLogisticsSupply ChainInformatikErziehung, Schul- und BildungswesenConference Paper10.15480/882.2943https://dl.gi.de/handle/20.500.12116/34190https://api.ltb.io/show/BMRWS10.15480/882.2943Zender, RaphaelRaphaelZenderIfenthaler, DirkDirkIfenthalerLeonhardt, ThiemoThiemoLeonhardtSchumacher, Clara SophiaClara SophiaSchumacherConference Paper