Kastner, MarvinFranzkeit, JannaLainé, AnnaZender, RaphaelIfenthaler, DirkLeonhardt, ThiemoSchumacher, Clara2020-09-082020-09-082020978-3-88579-702-9https://dl.gi.de/handle/20.500.12116/34190Teaching 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.enJupyter NotebooksCode LiteracyData LiteracyMachine LearningData ScienceLogisticsSupply ChainText/Conference Paper1617-5468