Damien Irving

Yeah, that's my concern too. `readings.py` is fairly short, so hopefully with some edits to the supporting text the changes will be obvious. If not, you can always just reject...

@maxim-belkin Sorry to be that person, but if I could delegate that would be great.

Here's the lesson recording: https://www.youtube.com/watch?v=TSw3GF_d2y8

@eldobbins Thanks for choosing to focus on improving the PyAOS lessons for your instructor training requirements! Thanks also for identifying the FIXME's in the contributing file - when I used...

Here's one for people who have never used Python before: https://swcarpentry.github.io/python-novice-gapminder/

Here's a list from the pangeo people: https://github.com/pangeo-data/education-material

The most mature lessons I've seen are the Siphon / Metpy lessons from unidata: https://unidata.github.io/python-workshop/ They have links to other relevant lessons on their general training page: https://unidata.github.io/python-training/

Here is a lesson on conda: https://kaust-vislab.github.io/introduction-to-conda-for-data-scientists/index.html

In terms of geospatial lessons: * Data Carpentry are developing a geospatial Python lesson to go with their well developed R geospatial lessons: https://github.com/carpentries-incubator/geospatial-python * There's a new textbook: https://pythongis.org/

The ARC Centre of Excellence for Climate Extremes have lessons on parallel processing: https://coecms-training.github.io/parallel All their training materials are at: https://github.com/coecms-training