Data Science and Energy: Some Lessons from Europe on Higher Education Course Design and Delivery

Data science is seen as a key enabler for technologies that help decarbonize global energy use. However, the energy sector continues to struggle to attract and train enough data scientists. The primary reason for this is the lack of emphasis on data science in most graduate programs in energy engine...

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Bibliographic Details
Published inHarvard data science review Vol. 4.1; no. Winter
Main Authors Kazmi, Hussain, Munné-Collado, Íngrid, Tidriri, Khaoula, Nordström, Lars, Gielen, Frank, Driesen, Johan
Format Journal Article
LanguageEnglish
Published MIT Press 27.01.2022
The MIT Press
Subjects
Artificial Intelligence
Computer Science
Engineering Sciences
Mathematics
Statistics
MOOC
STEM Education
TinyML
Applied ML
Edge AI
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Summary:Data science is seen as a key enabler for technologies that help decarbonize global energy use. However, the energy sector continues to struggle to attract and train enough data scientists. The primary reason for this is the lack of emphasis on data science in most graduate programs in energy engineering, and the high barriers of entry for data scientists from other sectors. In this paper, we present a snapshot of the data science related curriculum being taught in graduate energy programs in four different European universities as well as include feedback we received from students and alumni of these programs. While knowledge of data science remains low across the board, students in these programs already recognize data science as an important element of their future professional careers. We also present findings from running three separate iterations of an energy data science course we developed in light of this feedback – one of these iterations was offered only in KU Leuven (Belgium), while the other two were accessible to students at all four universities. In the paper, we also discuss challenges and opportunities arising from designing and delivering courses in a cross- university context. This foundational course and others like it are seen as a necessary means to enable students to take more specialized courses in data science, and eventually contribute towards realizing a sustainable energy transition and meeting climate change mitigation objectives.
ISSN:2644-2353
DOI:10.1162/99608f92.fd504fc4