Earth and Environmental Sciences
Undergraduate and Graduate Lecture
Tu 4:10-6PM
This course is a project-based learning course where teams of climate science and data science students collaborate to create machine learning predictive models for challenges inspired by LEAP's research. Students from different background will apply their prior knowledge, work together and teach each other in high-paced collaborative projects. Through a sequence of mini-projects, i.e., “challenges”, this course provides students a deeper understanding of using machine learning for climate science and support predictive capabilities. It provides training on a broad set of practical skills for climate data science research. It will also offer discussions on the opportunities and challenges of using climate science and projections in decision processes. No formal instruction on statistics, data science, machine learning, or climate science will be given.
Link to Vergil
Note: only courses offered during the two previous semesters have active Vergil links.
Please note: The Center does not administer the courses listed and is not responsible for any changes in the content. For more information, please check the course directory or reach out directly to the instructor.
