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An Open-Source AI/ML High School Curriculum Using Berkeley Lab STEM Research Data

May 19, 2026 · 3 authors · 7 topics

Due to the rapid advancements of Artificial Intelligence (AI), it is increasingly important to implement AI and Machine Learning (ML) curriculum into the classroom so that students are well-equipped for future careers in the Science, Technology, Engineering, and Mathematics (STEM) ecosystem. Since 2024, members of the K-12 STEM Education team at Berkeley Lab have been updating our data science curriculum for our high school summer program, the Berkeley Lab Director's Apprenticeship Program (BLDAP): Interdisciplinary Pathways to Machine Learning and Data Science (IPMLDS), to include Machine Learning (ML) challenge Jupyter notebooks. This paper details the three ML challenge notebooks created by scientists, engineers, and members of the K-12 team at Berkeley Lab. Our curriculum has been structured and continuously adapted so that educators can introduce it in their classrooms to address the gap in AI curriculum at the high school level.

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Sage MillerAlisa BettaleFaith Dukes
Teaching and Learning ProgrammingGeneticsBioinformaticsand Biomedical ResearchScientific Computing and Data ManagementCurriculumApprenticeship
PublishedMay 19, 2026
TypeArticle
Citations0

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