Spring 2022 (Syllabus)
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
- Introduction to LEAP CPC (Zheng)
- Introduction to Earth Systems and Climate Change (McKinley)
- Project 1 description Hurricanes and Clime Change starts
- Team activities
- Self introduction and a fun fact
- The LEAP crossword challenge
- Find a time to review and discuss project 1 materials as a group
- Tutorial on EDAV (Zheng)
- A deep dive into Project 1
- Project 1 starter codes (Jiaxu Li)
- Discussion and Q&A
- Presentation and submission instruction (Zheng)
- Team lightning shares
- Discussion and Q&A
- Project 1 presentations
- Project 2 starts.
- Introduction to Project 2 (McKinley and Zheng)
- [Tutorial] The physics of temperature stratification (McKinley)
- [Tutorial] A deep dive into Project 2's PGML (Zheng)
- Project 2 starters codes
- Discussion and Q&A
- [Tutorial] More on energy conservation (McKinley)
- Brainstorming, Discussion and Q&A
- Discussion and Q&A
- Project 2 presentations
- Project 3 starts.
- Climate Science Tutorial on "Air-Sea Flux of CO2" (McKinley)
- Discussion and Q&A
- Tutorial on decision tree, random forests and xgboost (Zheng)
- Review of starter codes (Xiaoshu Zhao)
- Discussion of papers and Q&A
- Q&A on starter codes (Xiaoshu Zhao)
- Discussion of research ideas
- Tutorials on explainable AI (Zheng)
- Q&A on research ideas (McKinley)
- Q&A
- Project 3 submission and presentations