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DeepLearning.AI · on Coursera

Generative AI for Everyone

4.8(24,100) on Coursera·380K enrolled
Beginner 6 hours English Course CertificateFREE
SkillsGenerative AIAI literacyPromptingAI applicationsAI at workResponsible AI

Is this course right for you?

Our take
Worth it if you want to understand generative AI clearly, without hype and without coding. It is free to audit and short.

Good for: anyone who wants a clear, non-technical understanding of generative AI.

Skip if: you want to build AI systems, or you already understand LLMs.

Andrew Ng explains at a high level how generative AI works, what it is good and bad at, how to use the tools well, and how teams can apply it responsibly. It is aimed squarely at decision-makers and anyone who wants understanding rather than a build tutorial.

It will not teach you to build AI systems — there is no programming — so follow it with a hands-on course if that is your goal, and if you already understand LLMs it will be too basic. The certificate needs a paid subscription; the free audit covers the learning. Ng keeps it updated as the field moves.

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About this course

Generative AI for Everyone is Andrew Ng's short, ~6-hour course on Coursera that explains generative AI in plain terms. You can audit it free; the certificate runs on the paid Coursera track.

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Instructor

AN
Andrew Ng
Coursera instructor

Andrew Ng co-founded Coursera and DeepLearning.AI and is one of the most trusted voices in AI education, known for clear, hype-free explanations.

Frequently asked questions

No, and that is deliberate. Andrew Ng built it for non-technical people, so there is no coding and no maths — just clear explanations of what generative AI is, how large language models actually work at a conceptual level, and where they succeed and fail. Anyone comfortable using a computer can follow it; the goal is understanding and judgement, not building models yourself.

They are separate courses for separate moments. The original AI for Everyone predates ChatGPT and covers AI strategy and traditional machine learning broadly. This newer one is focused squarely on generative AI and large language models — prompting, real use cases, and how to think about adopting these tools. If your interest is today's ChatGPT-style AI, this is the relevant one to take.

Yes, and more than surface tips. Alongside hands-on prompting practice for everyday work, it covers how to think about generative AI projects end to end and introduces retrieval augmented generation, or RAG, which is the dominant pattern behind most serious business AI applications. That grounding is what lets you have a sensible conversation about where these tools fit at work, rather than just typing prompts.

Yes. The video lessons can be audited free on Coursera, so the entire teaching content costs nothing to watch. You only pay, around forty-nine US dollars, if you want the graded elements and the shareable certificate. Given it runs only about six hours, auditing it is an easy recommendation even if you never bother with the credential.

For almost any professional who works alongside AI rather than building it, yes. In roughly six hours it gives you a defensible, plain-English mental model of what generative AI can and cannot do, plus the vocabulary to contribute to decisions about it at work. It will not qualify you for a machine-learning engineering role, but that was never its purpose.
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