2026/07/24 by Peter Wulff, Paul Wulff
paper · doi:10.1088/1361-6404/ae9014
Abstract Artificial Intelligence (AI) has become an important modeling tool in physics. This article is intended as a research-informed instructional proposal on teaching about AI use cases in physics for upper-level undergraduate physics students. Four exemplary use cases are presented, where students can learn in what ways AI can facilitate data-driven and physics-informed modeling for physical systems with an emphasis on instructional goals and limitations of AI. Our work builds on prior curriculum suggestions for data-driven physics and knowledge on AI usage in physics. We seek to provide guidance for physics instructors and students on potentials and limitations of AI in physics, and how to implement AI models for the respective use cases.