W3Schools is probably the most familiar name on this entire list, because almost anyone who has ever searched for how to do something in Python or HTML has landed on one of its pages, and that ubiquity is exactly why it is worth being clear about what it is good for and what it is not. As a reference it is genuinely handy, with a clean layout, a try it yourself editor that lets you run snippets in the browser, and Python pages that are perfect for the quick lookups we all do dozens of times a week when we cannot quite remember the argument order of a function. Its introductory machine learning and data science sections do a reasonable job of easing a complete beginner into the basic vocabulary, walking through concepts like mean, median, and standard deviation, simple regression, and the general shape of a machine learning workflow in plain language, and for someone who has never seen any of this before that gentle first exposure has some value. The problem is that the depth simply is not there.
The coverage is a mile wide and an inch deep, the machine learning pages stop almost as soon as they start, and in the pursuit of simplicity the explanations occasionally sand off so much nuance that they become a little misleading, which is a real risk when you are trying to build correct mental models. The experience is also cluttered with advertising and persistent nudges toward the paid certifications and the Plus subscription, neither of which carries much weight with employers. There is no meaningful project work, no sustained progression, and nothing that would take you from curious beginner to someone who can actually build and evaluate a model. My honest take is that W3Schools earns its place as a reference and a first glance, and I still open it regularly for exactly that, but it should sit alongside a real course rather than pretending to be one, because on its own it will never get you close to genuine AI competence.