This is meant to be a living document if you have any suggestions please open an issue or send a PR! 👍
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(course - Free) Python for Data Science (UCSD) EdX.org class:
- Link: https://www.edx.org/course/python-for-data-science-0
- Notes: Archived version. Designed to be 8-10 hours of effort/work per week but you can go at your own pace.
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(article) Towards Data Science: Python Basics for Data Science:
- Link: https://towardsdatascience.com/python-basics-for-data-science-6a6c987f2755
- Notes: It's a pretty good primer on the basics of python (data types, functions, methods, etc). It serves well as a reference sheet in the future.
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(course - Not Free -- usually $9.99) Python for Data Science and Machine Learning Bootcamp:
- Link: https://www.udemy.com/python-for-data-science-and-machine-learning-bootcamp/
- Notes: Jose Portilla from Pieran Data (his startup I think) has a bunch of great courses on Udemy. They are all usually "on sale" at $9.99 and even though it's not free it's a pretty good deal because you go from very beginner python to some powerful machine learning algorithms (if you understand the basics of programming in any other language you'll be ok).
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(course - Free -- 4 hours total) Intro to Python by DataCamp:
- https://www.datacamp.com/courses/intro-to-python-for-data-science
- This is a very short intro course (4 hours total) but it'll get you started on the right track.
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(online platform) https://codechalleng.es
- These are a bunch of bite-sized exercises to "hone your python skills in the comfort of your own browser"
- Not focused in data science but I find it useful to not forget simple details.
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(tutorials) Data Science tutorials at Real Python:
- https://realpython.com/tutorials/data-science/
- Real Python's website has been adding more and more tutorials regarding data science. They are focused on specific tasks (reading/writing CSV files, cleaning data, text classification, etc) and they are very thorough. These are text tutorials, not video.
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(video tutorials) Corey Schafer's youtube channel:
- beginner python series: https://www.youtube.com/watch?v=YYXdXT2l-Gg&list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7
- Corey Schafer's channel is full of tutorials on all things related to software development (git, command line, python, javascript, etc).
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(video tutorials) PyCon and SciPy:
- These tutorials last about 3 hours (there's a lot of downtime between exercises) and their code is on GitHub. You can follow along at your own pace and they're a pretty good start in general. Especially if you already know some programming.
Pandasfor Data Analysis (SciPy 2017) - https://www.youtube.com/watch?v=oGzU688xCUs- Intro to
pythonand Programming (SciPy 2018) - https://www.youtube.com/watch?v=Xmxy2NU9LOI Pandasfor Data Science (PyCon 2018) - https://www.youtube.com/watch?v=0hsKLYfyQZc
- These tutorials last about 3 hours (there's a lot of downtime between exercises) and their code is on GitHub. You can follow along at your own pace and they're a pretty good start in general. Especially if you already know some programming.
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(blog posts) Anna-Lena Popkes -
- She did a #100DaysOfCode challenge to learn
python(for machine learning) and documented her journey in a series of blog posts where she created a "magical world" to explain what a Class is, inheritance, functions, etc. It's very easy and entertaining to follow.- Day 1: http://alpopkes.com/posts/2018/07/coding-challenge-day-1/
- GitHub: https://github.com/zotroneneis/machine_learning_basics
- She had an interview on Talk Python to Me (podcast - ⭐⭐⭐⭐⭐ 100% recommend) where she explains the whole thing https://talkpython.fm/episodes/show/186/100-days-of-python-in-a-magical-universe
- She did a #100DaysOfCode challenge to learn
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(examples) Lots of python code snippets to study, recreate, or save you when you're stuck
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(online courses - Free) Multiple tracks to learn many different Data Science skills -