I came to 365 Data Science expecting another video library and found something a bit more thoughtful. The whole platform is built around a single sequence that starts with the boring but essential foundations, statistics and probability, then moves you through Python and SQL, into machine learning, and more recently into AI and large language model territory. That ordering is the point. Most beginners I talk to are drowning in choice, jumping between random YouTube playlists and never finishing anything, and the value here is that someone has already decided what you should learn and in what order.
The lessons themselves are short and cleanly produced, the kind you can knock out a couple of in a spare half hour, and the instructors do something I appreciate. They actually explain why a model works, the maths and the intuition underneath it, instead of rushing you to copy and paste code you do not understand. The certificate and the career tracks give the whole thing a finish line, which helps with motivation more than people admit. Where I temper my enthusiasm is the practice.
A lot of the exercises are quizzes and guided walkthroughs that test whether you followed along, not whether you can sit at a blank editor and solve something messy. You can come out of a track feeling like you know machine learning and then realise you have never actually built a model end to end on your own data. The catalog is also smaller than the big platforms, so once you finish the core path you will outgrow it faster than you would DataCamp or Coursera. On price, the monthly rate is steep for what you get, but they run the annual plan at a discount often enough that the real cost is closer to fair, and that is the number to wait for.
My honest take is that 365 Data Science is one of the better structured starts in this space, as long as you treat it as the foundation and then push yourself onto your own projects, because that is the part no platform can do for you.