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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
today I choose violence

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Seems like you plan to use Python in data science. I recommend a course on udacity. The name is something like Python for data science. The key is to get hands dirty, constantly running things.
Coach
Datacamp is good. Working through one of the free Python books online is good. Practice with leetcode or hackerrank. Do some course with data structures, not just a super-applied data science course. Do projects on your own. Use functions and write clean, testable, maintenable code -- it's free to do, always worth it, and it'll make you look like a better programmer than you actually are.
I second datacamp. and they're doing a huge sale right now - a little pricey at $150, but a very good value for a full year if you plan to actually follow through on learning (unlike me and my stupid nagging Duolingo owl)
Go and check out Kaggle. It’s a great resource where you play around with any datasets and see others’ works for inspiration. Also, try to use Python in your current job like automation for running reports or a tool for data cleaning/preprocessing.
Thank you so much for mentioning Kaggle, this is really cool! Cheers!
Try this as an exercise
https://pbpython.com/monte-carlo.html
Honestly I think Wes McKinney's book "Python for Data Analysis" is the best option for learning pandas. Wes wrote pandas and this book is the best showcase of it.
So often I see people implementing functionality they don't realise is actually in-built with pandas and going through the code in this book will help avoid that.
https://towardsdatascience.com/4-free-courses-i-took-to-learn-python-for-data-science-bcbcc7825476
https://automatetheboringstuff.com
It gives you some good practical examples
There’s a good course on Udemy; I taught myself by thinking of simple projects and googling around till I solved the project.
If you have some programming background, you can learn Python yourself, but I would still recommend to learn it by watching some good tutorials. Pandas and matplotlib are typically used for data science and ML projects. Udemy is a good resource to learn. Here’s an example
https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
Datacamp
Don’t focus on pandas if you want to learn python. Focus on object oriented programming, class development, DRY code.