Stanford Online's AI Professional Program is one of the few cases where the brand on the certificate matches the substance behind it. The courses are built on the same material Stanford teaches its graduate students, things like XCS221 Artificial Intelligence Principles and Techniques and XCS229 Machine Learning, and what you get is the real thing rather than a marketing-friendly summary of it. I respect that they did not dumb it down to widen the audience. The trade-off is that this is hard work.
The assignments are graded, the maths is real, and you are expected to write actual code, so if your linear algebra and probability are rusty or your Python is shaky, you will feel it quickly. My honest advice is to watch a few of Andrew Ng's free CS229 lectures on YouTube before you pay anything, because Stanford has put a lot of this teaching out in the open, and those lectures are the single best way to find out whether the level suits you. The cost is the part that makes people hesitate, and rightly so. At roughly 1,950 dollars per course, completing the full program is a four-figure commitment that stretches well past what most online courses charge, and you are paying for the rigour, the graded feedback and the Stanford name rather than for content you could not find anywhere else.
For a working engineer who wants to move into machine learning properly and wants a credential that will not get a raised eyebrow from a hiring manager, that premium can be worth it, especially since an employer learning budget often covers it. Where I would steer people away is if they are beginners or non-technical. This program assumes a baseline that a lot of AI courses do not, and someone who simply wants to understand and use AI tools in their job will get far more value, far faster and far cheaper, from something like Google AI Essentials or Generative AI for Everyone. Pick this when you specifically want graduate-level depth and a serious certificate, and only then.