Course material I created, instructed, and graded at the University of Washington in Winter 2019. The course is designed to equip students with the skills needed to conduct sophisticated oceanographic research using Python.
The course material consisted of how to:
- Write scalable code using functional programming
- Use appropriate code style (function docstrings, proper variable naming, using a main function to execute code)
- Use numpy, matplotlib, xarray, pandas, scipy
- Create complex plots of oceanographic data (cross sections, maps, time-series, vertical profiles)
- Work with dictionaries and multi-dimensional arrays to analyze geospatial oceanographic data
- Read and write data to various file types (csv, netCDF, cnv)
The course syllabus and assignments are posted to this page.
In the future, a few example assignment outputs will be found below.
I also worked with the chair of the Informatics program at the University of Washington, Andy Ko, to study my teacher identity development throughout this entire process, as I taught this course grounded in data science while also learning how to teach.