The Data Engineering Cookbook
Andreas Kretz,
Team Data Science, GitHub,
Sept 28, 2020
This is a sprawling epic of a guide, running the gamut from programming tools to machine learning to best practices to case studies. It's on GitHub so you could (if you wanted) clone it and make your own version, or (better) suggest changes and improvements. There's also a PDF version (but note that it will ask you to sign up to the newsletter before you can download it). What I like about this is that it's the sort of thing you could set an interested team of high school students on for a semester and see what they come up with. Wouldn't that be so much better for them than watching lectures on Zoom?
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