UBC-MDS / UBC-MDS/programming-in-python-for-data-science
Comments on the syllabus
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Description
Comments on this document:
- I would move
applyandapplymaplater. It's a more advanced concept I think. Also, a lot of times you can just do things likedf['new'] = df['old'] ** 2(or whatever) - For the missing values (and one-hot encoding), there's the pandas way and the scikit-learn way. We should decide which one we're doing. If the latter, I guess we don't need to teach the pandas way?
- Do we want/need regular expressions?
- Module 6 looks too full to me. Functions are easily their own module IMO. I might move a bunch of it to Module 8.
- Do we want/need broadcasting? For module 7, this might be their first time thinking about array shapes and dimensions.
Thanks @hfboyce !
cc @ttimbers
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Research direction
Start with docs/syllabus-learning-outcomes.md and review the comments about apply, applymap, missing values, one-hot encoding, regular expressions, functions, and broadcasting. Done means reaching and documenting clear decisions about the module placement and topics to teach.
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Assessment
- Tech stack
- numpy, pandas, python, scikit-learn
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100