Teaching

SIO Courses

SIO(c) 209 - Deep Learning for Environmental/Geo Science

This course introduces students to the theory and practice of deep learning for environmental and geoscience applications. The course will cover the basics of deep learning, including neural networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks. The course will also cover the use of deep learning for image analysis, time series analysis, and (briefly) natural language processing. The course will include a mix of lectures, hands-on exercises, and a final project.

• We broadly follow our new course book here, which is still being refined.
• SIO 209 specific material can be found here

HDSI Courses

DSC 200 - Data Science Programming

Computing structures and programming concepts such as object orientation, data structures such as queues, heaps, lists, search trees and hash tables. Laboratory skills include data analysis with pandas and xarray in Jupyter notebooks.

• The syllabus for this course is available here.
• Please see course canvas page for details: https://canvas.ucsd.edu/courses/49102
• Github repo: https://github.com/climate-analytics-lab/dsc200-fa23-public/

DSC 180A - Data Science Capstone

Data science capstone course. Students work in teams to complete a climate related data science project. Project management, communication, and teamwork skills are emphasized.

• Please see course page here for details.