SDG Detail

Environmental Data Science Practicum I

None

Project description

Research in climate and environmental sciences is increasingly focused on analyses of complex spatio-temporal data, with satellite observations and detailed numerical simulations providing datasets whose size may reach the Tb range. Relevant research questions also increasingly span disciplinary boundaries. This project-based course is intended to provide students with a structured research experience in working with complex environmental data on a project that should lead to publishable science. The course is the first course of a two-course sequence with GEOS 39660 to be taken in the Spring. Students enroll individually and then form interdisciplinary groups. During the two quarters, groups will work on research projects with guidance from University faculty members and external researchers. Lectures and exercises cover topics in statistics, computer science, data science, and research practices. The course is a requirement for Ph.D. students participating in the University�s NSF Research Traineeship program in Computational Training for Energy and Environmental Sciences but enrollment is open to all graduate students, space permitting. Students enrolled in GEOS 39660 for Spring quarter are encouraged to enroll concurrently in GEOS 39600, Science Writing Practicum, which will guide them through completion of a manuscript for submission