Seconding the recommendation above! Theory matters cuz without the math logic, ML models are basically just black boxes. Unfortunately, I’ve had issues with many apps being too 'gamey' and skipping industry standards. For a budget-friendly route with more depth: - Sololearn: Learn to Code is great for Python syntax.
- Coursera Mobile App - you can actually audit university-level ML courses for free! It’s way better for real depth tbh. gl!

In my experience, Enki: Learn Data Science & AI is a decent option. It covers technical ML concepts like regression really well for commuters. Honestly, it works well lol

In my experience, these are your best bets:
- DataCamp: Learn Data Science is highkey the best for Python and ML integration. It's sooo structured.
- Brilliant: Learn Interactive is actually awesome for the theory side... it makes the jargon make sense.
Honestly, I've tried many over the years and these two give REAL depth. gl!

Re: "Helpful thread 👍" - agreed. I've spent over a decade in engineering, and honestly, the "app" approach can be a bit of a trap if you aren't careful. In my experience, there is a massive divide between the "gamified" brands and actual development environments. I spent months on those apps before realizing I couldn't even define a simple tensor or explain a gradient descent properly. My current setup involves using a cloud-based environment like Google Colab in a mobile browser. It is less "structured" than a curated course, but it forces you to deal with real-world Python libraries and actual documentation. I actually tracked my learning progress once and noticed my retention for ML logic was significantly higher when I stopped using the simplified interfaces. TL;DR: Most commute-friendly apps are too light on theory. I've had way better results using cloud notebooks to practice real code, even if the UI is clunkier.

Helpful thread 👍