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

H. Kazmi, Ingrid Munné-Collado, Khaoula Tidriri, L. Nordström, F. Gielen, J. Driesen
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Abstract

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 article, 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 article, 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 toward realizing a sustainable energy transition and meeting climate change mitigation objectives.
数据科学与能源:欧洲高等教育课程设计与教学的经验教训
数据科学被视为帮助全球能源使用脱碳技术的关键推动者。然而,能源行业仍然难以吸引和培养足够的数据科学家。造成这种情况的主要原因是大多数能源工程研究生课程缺乏对数据科学的重视,以及来自其他领域的数据科学家的高进入门槛。在这篇文章中,我们简要介绍了欧洲四所不同大学的研究生能源项目中正在教授的数据科学相关课程,以及我们从这些项目的学生和校友那里收到的反馈。虽然数据科学的知识仍然很低,但这些项目的学生已经认识到数据科学是他们未来职业生涯的重要组成部分。我们还介绍了我们根据这一反馈开发的能源数据科学课程的三个独立迭代的结果——其中一个迭代仅在比利时鲁汶大学提供,而其他两个迭代则对所有四所大学的学生开放。在本文中,我们还讨论了在跨大学环境中设计和交付课程所带来的挑战和机遇。这门基础课程和其他类似课程被视为使学生能够学习更多数据科学专业课程的必要手段,并最终有助于实现可持续能源转型和实现减缓气候变化的目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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