Codecademy has been the friendly front door to programming for years, and its AI and machine learning catalogue follows the same formula that made the platform popular. You learn inside an interactive editor in the browser, you type a few lines, you run them, and you get told straight away whether you got it right. For someone who has never written a line of code, that loop is genuinely valuable, because the single biggest thing that stops beginners is the friction of getting set up, and Codecademy removes all of it. The AI-relevant content includes Learn Python, an introduction to generative AI, building chatbots with Python, and a longer machine learning and AI engineer career path, plus their own AI assistant that can nudge you when you are stuck.
As a way to find out whether this stuff is for you at all, it is hard to beat. My reservations are about what happens after those first few weeks. The thing that makes Codecademy so welcoming, the sandboxed in-browser environment, is also the thing that holds it back, because real machine learning work happens in your own environment with your own messy data and error messages that nobody has pre-written a hint for. Codecademy never makes you build that muscle.
The AI and ML modules themselves are also noticeably more introductory than what you get on a platform built specifically for machine learning, and they stay light on the maths and the theory that you eventually need. And while the free tier is more generous than people expect, the structured paths and the better projects are mostly Pro, so to get real value you are paying a monthly subscription. None of this makes it bad. It makes it a particular kind of good.
If you are a true beginner who finds the setup of a normal coding environment off-putting, start here, get comfortable, and then deliberately graduate to something that forces you to work the way practitioners actually do.