4 minutesUsing AI Wisely for School Success
State one rule of thumb for telling AI homework help apart from AI cheating.
Stanford Online. Andrew Ng, one of the people who actually built the field, talking plainly about what AI is good at, what it isn't, and where the realistic opportunities sit. A useful counterweight to social-media takes — same calm, no-hype tone as the article, just with more depth on the "where is this actually going" question.
A 2023 talk, so treat the example applications as a snapshot; the calm what-AI-is-good-at framing is the part that holds up and the reason it stays.
You leave with a realistic sense of what AI is good at today, where it falls short, and which opportunities are worth taking seriously.
None — watchable cold, though it lands better after the primary pick's eight-minute mental model.
Last reviewed: May 18, 2026
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Hand-picked external courses that go deeper on this topic.
Andrew Ng
Real time inside an LLM, learning to prompt deliberately and recognise where generative AI is genuinely useful versus where it's a trap. Calm, no-hype teaching — the perfect bridge from "I've tried ChatGPT once" to "I use it every day with confidence."
Antje Barth · Shelbee Eigenbrode · Mike Chambers · Chris Fregly
When practitioners ask "what should I take if I'm serious about building with LLMs?", this is the answer. Mathematically honest without being a research paper; AWS-flavoured deployment chapters stay useful even if you'll never touch SageMaker.
Google Cloud
Google's own answer to 'what is generative AI, actually' — the non-technical counterpart to Elements of AI, aimed explicitly at sales, HR, marketing, and operations roles rather than engineers. Forty-five minutes to a real mental model of how generative AI differs from classic machine learning, with no code and no jargon.