Our AI course reviews each carry a scored verdict, a verified price, and at least one honest criticism — because a review with no negative isn’t a review, it’s an ad. That holds for the AI certification reviews too, MIT and NVIDIA and PMI included: same scoring, same required negative. We don’t claim to have sat through hundreds of hours we didn’t. Instead we mine every credible student report we can find, read the syllabus and pricing page ourselves, and score the consensus. Where we did complete a course, we say so.
Prices and certificate terms are re-checked monthly; the date on each page tells you when. Below is every course and certification we’ve put through that process so far. One rule we don’t break: if a course has no honest downside worth naming, it doesn’t earn a verdict — it gets left off. Comparing two of them directly? The comparisons shelf settles head-to-heads. New to all of this? Start at the courses directory.
All our AI course reviews
- IBM AI Engineering Professional Certificate — Coursera’s deep-end engineering track: real cost, time to finish, and what’s gone stale.
- Google AI Essentials — what $49 and a few hours actually buys, plus the free alternative path.
- Khan Academy AI courses — genuinely free, but who the level is really built for.
- Maxime Labonne’s LLM course — GitHub’s favorite roadmap: prerequisites and how to turn a repo into a study plan.
- MIT AI certificate programs — $2,500+ prestige weighed against cheaper paths that compete.
- Stanford AI classes — what outsiders can actually access, free lectures included.
- NVIDIA AI certifications — the GPU-skills track and how recruiters read it.
- PMI AI certification (CPMAI) — does it move the needle for PM hiring?
- OpenAI courses & “certification” — what actually exists versus rumor.
- NotebookLM training — paid courses versus the free path for a tool you can learn in a day.