The program offers a unique hybrid format, combining six weeks of virtual learning with two weeks of intensive in-person project work and presentations at the University of Minnesota, along with a stipend, housing, meals, and travel reimbursement for the in-person component.
The AI for Earth Summer School is an eight-week program designed to introduce students to the potential of AI/ML research for addressing environmental challenges. The program combines virtual and in-person sessions, offering hands-on experience in applying machine learning to environmental problems through tutorials and a small group project. Students will gain awareness of potential advances in AI/ML needed for environmental challenges, sufficient research experience and exposure to ML techniques to pursue further research, and the ability to work with large datasets on societally relevant problems. The curriculum includes topics such as recurrent neural networks in hydrology, convolutional neural networks in agriculture, graph neural networks, and generative AI and foundational models. Participants will develop skills in computer science fundamentals, Python programming, linear algebra, and calculus, and will work on group projects from week 3 to 8, culminating in final presentations.
During the virtual weeks, students will engage in approximately 20 hours of work per week, including 2 hours of lectures and 1 hour of tutorials. The in-person weeks will be full-time, 40 hours per week, with guest lectures, project work, and final presentations.
This program is ideal for undergraduate students (freshmen and sophomores encouraged) with a background in computer science fundamentals, Python, linear algebra, and calculus, who are highly motivated to apply machine learning to environmental problems.
University of Minnesota, 4-192 Keller Hall, 200 Union Street SE, Minneapolis, MN 55455
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