Insights into the design of an introductory course for data science and machine learning for engineering students - Archive ouverte HAL Access content directly
Conference Papers Year : 2022

Insights into the design of an introductory course for data science and machine learning for engineering students

Katharina Bata
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  • PersonId : 1156183
Angela Schmitz
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Andreas Eichler
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  • PersonId : 978363

Abstract

Due to their interdisciplinary nature, data science methods, such as machine learning, can be taught in many different ways. This paper presents an approach that takes advantage of the close content connection to statistics and of the mathematical structure of data science methods to develop an introductory course for engineering students. Following the research methodology of design research, we discuss the theoretical motivation and methodological implementation of the design principles for the course and show first insights into empirical results from the design cycles.
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Dates and versions

hal-03751807 , version 1 (15-08-2022)

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  • HAL Id : hal-03751807 , version 1

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Katharina Bata, Angela Schmitz, Andreas Eichler. Insights into the design of an introductory course for data science and machine learning for engineering students. Twelfth Congress of the European Society for Research in Mathematics Education (CERME12), Feb 2022, Bozen-Bolzano, Italy. ⟨hal-03751807⟩

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