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UdemyAround 25 hours of video, self-paced·Around $15 to $20 on frequent sale, list price much higher

Python for Data Science and Machine Learning Bootcamp

4.4

This is the course that taught a generation of people the Python data stack, and it is still one of the best value entries into the field. The teaching is clear and the breadth is huge, though parts of the deep learning material now show their age.

What We Liked

  • Outstanding value, regularly available for the price of a takeaway
  • Jose Portilla is a famously clear, calm, well-paced instructor
  • Broad coverage from Python and Pandas through to core machine learning
  • Lifetime access means you can return and revisit modules whenever you like

What Could Be Better

  • The deep learning sections have aged and lag behind current tooling
  • Breadth means each topic gets foundations rather than true depth
  • Heavier on using libraries than understanding the maths underneath
  • No live support or accountability, as with any self-paced Udemy course

Detailed review

If you ask a room of self-taught data people how they started, a startling number will name this exact course, and for good reason. Jose Portilla has a teaching style that is calm, clear, and perfectly paced, the kind that never makes you feel stupid for not getting something the first time, and over its long life this bootcamp has walked an enormous number of complete beginners from never having written Python to comfortably wrangling data with Pandas, visualising it, and training their first machine learning models with scikit-learn. The breadth is genuinely impressive for the money, covering the core Python data stack of NumPy, Pandas, Matplotlib, and Seaborn before moving into the main families of machine learning algorithms, and because Udemy discounts so aggressively you can usually pick the whole thing up for less than the cost of lunch. Lifetime access means it becomes a reference you return to, not just a course you finish once.

The honest caveats matter though. This course has been around a long time, and while the Python and classical machine learning material has aged gracefully, the deep learning sections feel distinctly dated next to how the field actually works now, so I would not lean on them as your primary source for neural networks. The breadth that makes it such good value also means depth is sacrificed, and you come away with solid foundations across many topics rather than mastery of any one of them. It leans toward teaching you how to use the libraries rather than the mathematics underneath, which is fine for getting productive but leaves a gap you will eventually want to fill.

And like every self-paced Udemy course, there is no accountability, so finishing it is entirely on your own discipline. My verdict is unchanged from why it became a classic in the first place. As a first serious step into Python for data science and machine learning, especially at the sale price, it remains one of the best deals in online education. Just treat the deep learning chapters as historical context and reach for something current once your fundamentals are solid.

[ final ]

The verdict.

Still one of the best first steps into Python for data and machine learning, especially at the sale price. Pair it with a more current deep learning resource once you have the fundamentals down.