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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.

• (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.

• (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).

• (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.

• (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.

• (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.

• (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).

• (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.
    • Pandas for Data Analysis (SciPy 2017) - https://www.youtube.com/watch?v=oGzU688xCUs
    • Intro to python and Programming (SciPy 2018) - https://www.youtube.com/watch?v=Xmxy2NU9LOI
    • Pandas for Data Science (PyCon 2018) - https://www.youtube.com/watch?v=0hsKLYfyQZc

• (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:https://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

• (examples) Lots of python code snippets to study, recreate, or save you when you're stuck

  • https://www.pythonprogramming.in/

• (online courses - Free) Multiple tracks to learn many different Data Science skills -

  • https://cognitiveclass.ai/