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OtherSelf paced, a large free YouTube library of individual tutorials and structured playlists ranging from short single topic videos to hour long deep dives·Free on YouTube, supported by an optional membership and the occasional sponsor

Corey Schafer (Python Programming Tutorials)

4.6

If you want to learn Python properly rather than just copy snippets, Corey Schafer is about as good as free teaching gets. The explanations are calm, precise and unusually thorough, and while this is not a machine learning course, it builds the Python, Pandas and tooling foundation that almost every AI course assumes you already have.

What We Liked

  • Exceptionally clear, well paced teaching that explains why things work, not just what to type
  • Deep, authoritative coverage of core Python and key libraries like Pandas and Matplotlib that data and ML work relies on
  • Individual videos and playlists are well organised, so you can learn a topic in order or drop in for one specific thing
  • Completely free, with no filler and a signal to noise ratio that shames a lot of paid courses

What Could Be Better

  • It is a Python and tooling channel, not a machine learning one, so you will not find model building courses here
  • The upload pace has slowed a lot in recent years, so some newer language and library features are not covered
  • The measured, comprehensive style can feel slow if you only want a quick answer
  • As a YouTube library rather than a course it has no assignments, projects or structured path to completion

Detailed review

Corey Schafer is one of those educators that experienced developers quietly recommend to beginners over almost anything else, and the reason is simple, the teaching is just very good. The channel is not about chasing trends or building flashy end products, it is about explaining Python and the tools around it clearly and thoroughly, and it does that better than most paid courses I have seen. What sets it apart is the patience and precision of the explanations. Rather than racing to a result, Corey tends to explain what is actually happening underneath, why a feature exists, and how the pieces relate, so you come away understanding the language rather than just having copied a working example, and that kind of foundation pays off for years.

The coverage is exactly the part of the stack that trips people up when they jump into AI, including core Python properly done, object oriented programming, decorators and the language features people usually fudge, plus the data workhorses like Pandas and Matplotlib and the surrounding tooling such as Git, virtual environments and development setup. None of that is machine learning, and that is the honest caveat to be clear about, you will not find a course here that walks you through training models or building a neural network. What you will find is the reason so many people fail at those courses solved, because most of the pain in an ML course is not the machine learning, it is weak Python, clumsy data manipulation and a shaky development environment, and this channel fixes precisely those things. The two limitations worth naming are both mild.

The upload cadence has slowed considerably over the last few years, so while the fundamentals it teaches are essentially timeless, some of the newest language and library features are not covered, and you may occasionally need to top up from elsewhere. And because it is a YouTube library rather than a designed course, there is no assignment track, no projects and no formal path to completion, so you have to bring your own structure and practice. The measured pace that makes the teaching so clear can also feel slow if you only came for a one line answer, though that same thoroughness is exactly why the material sticks. My take is that Corey Schafer is one of the highest value free resources in this whole space, not despite being a Python channel rather than a machine learning one, but because of it.

Before you spend money on a machine learning course, spend time here getting genuinely comfortable with Python, Pandas and your tooling, and you will get far more out of everything you study afterwards. Rated as what it is, a free foundation in the language that underpins modern AI, it is close to essential.

[ final ]

The verdict.

One of the best free investments you can make before touching a machine learning course, because so much of the struggle in AI learning is really shaky Python. Work through the core Python and Pandas playlists until the language feels natural, then take that foundation into a dedicated ML course.