Data Science for Geoscience
Do you want to acquire skills that can make a difference in today's world? How can we use big data to find the next major mineral deposits of Cobalt that will drive the battery revolution? Can data from geochemical analysis reveal the polluting factors of the central valley groundwater system? Can past data from landslides or fires reveal a climate change signal, and can they be used to predict future events?
Data Science for Geoscience provides the statistical and machine learning foundation that addresses questions like these with actual case studies. It covers areas of data science typically not found in computer science courses and focuses on the geoscientific as well as human and societal relevance.
Two courses offered: Undergraduate [GEOLSCI 6 / EARTHSYS 100A] and Graduate Students [GEOLSCI/ENERGY/EARTHSYS 240 / ESS 239]
Taught by Professor of Earth and Planetary Sciences Jef Caers.
See what students who took the course had to say...
“This course improved the way I think about answering questions in the Earth Sciences within a statistical framework. I enjoyed that the lectures used specific applications as examples and that the focus included the bigger picture rather than just the details of the math.”
“Jef Caers is one the best instructors I've ever had for any subject ever. He covers really useful and challenging concepts, but because of his incredible teaching skills, the more difficult concepts feel more approachable.”
"Jef cares about how we progress as students, more as lifelong learners than limited to the course. He also is really good at promoting his students and helping them grow as students, researchers, and educators."