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Computer Science (Sci) : Applications of machine learning in fighting climate change, including use cases in electricity systems, buildings, transportation, agriculture and other land use, disaster response, and other areas. Review of recent research literature, with emphasis on when machine learning is relevant and helpful, and how to go about scoping, developing, and deploying a project so that it has the intended impact.
Terms: Fall 2024
Instructors: Rolnick, David (Fall)
1. This course is aimed at graduate students with at least some prior experience in machine learning and ability to read and assimilate research literature across many areas of machine learning. Prior experience with climate change-related topics is not required, but willingness to learn about these topics is.
