GEOG 473/673 was a graduate level programming course I created from scratch and taught at the University of Delaware between 2019 and 2022. It covered roughly 4 credits worth of a tutorial based course where the students were taught how to approach geospatial and environmental specific coding problems. Data analysis, spatial reprojection, statistical analysis, visual analysis, and machine learning were all topics covered in the course.

Open Source Textbook:

https://jsimkins2.github.io/geog473-673/r-for-geospatial-sciences.html

Lecture & Tutorial Videos:

https://www.youtube.com/watch?v=alIUwMMnq7M

I also created and taught a Python course for environmental sciences between 2019 and 2022. This course was roughly 2-3 credits worth of tutorials focused on covering popular Python packages and how they can be used for geospatial/environmental purposes. NumPy, Xarray, Matplotlib, SciPy, MetPy, etc. are all covered in this class.

https://github.com/jsimkins2/geog473-673/tree/master/Python