Microsoft · on Coursera

Microsoft Generative AI Engineering Professional Certificate

4.4(17) on Coursera·10K enrolled
Intermediate 101 hours English Professional Certificate
SkillsAzure AIPrompt engineeringFine-tuning LLMsMLOpsModel deploymentResponsible AIMultimodal AI

Is this course right for you?

Our take
Microsoft's five-course path to building and shipping generative AI specifically on Azure.

Good for: Intermediate developers aiming for Azure-based generative-AI engineering roles.

Skip if: You work outside the Azure ecosystem or you're a complete beginner.

It runs through prompt engineering, fine-tuning, deployment and MLOps, with responsible AI and security threaded throughout — a genuinely end-to-end engineering arc. The key qualifier is in the framing: it's opinionated toward Microsoft's ecosystem, so its value is highest if you're targeting Azure-based AI roles and lower if you work outside that world or you're a complete beginner.

Audit the courses free on Coursera; the professional certificate needs a paid subscription (around $49/month or Coursera Plus). It's a strong signal for Azure-oriented AI roles specifically, and as always demonstrated projects weigh alongside it. A newer (2026) certificate, so there are relatively few reviews to go on yet (as of 2026).

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About this course

The Microsoft Generative AI Engineering Professional Certificate is a five-course series that takes GenAI from prototype to production on Azure. It spans prompt engineering, fine-tuning large language models, multimodal integration, model deployment and MLOps, with a consistent thread of responsible AI, AI security and data ethics running through it.

Instructor

M
Microsoft
Coursera instructor

This certificate is produced by Microsoft, drawing on how its own teams build and ship generative-AI systems on Azure — which is why the curriculum is closely tied to Azure AI services and production practices.

Frequently asked questions

If you're targeting AI roles at companies invested in Microsoft/Azure, yes — the curriculum-to-job-requirements match is strong and it's very hands-on inside the Azure AI ecosystem. It's aimed at getting your foot in the door for entry-to-mid roles; think stepping stone plus a portfolio, not a guarantee.

Python and a foundational understanding of Azure — and these are real prerequisites, not soft suggestions. If you're missing Azure basics, spend time on Microsoft Learn's free Azure fundamentals first; trying to learn Azure and GenAI engineering at once slows you down a lot.

They're easy to confuse. This one is generative-AI-focused — prompt engineering, fine-tuning, multimodal and deployment on Azure. The broader AI & ML Engineering certificate covers more general machine-learning engineering. Pick this if your target is specifically GenAI application work.

Yes — you spend most of the time inside the Azure AI ecosystem. That's a plus if your target employers use Azure, and a drawback if you work with AWS or Google Cloud instead.

You can audit the courses free on Coursera; the certificate needs a subscription (around $49/month or Coursera Plus). It's about 100 hours across five courses — roughly three months at a few hours a week.
Paid
Free to audit · paid certificate
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