COMicrosoft · on Coursera
Microsoft Generative AI Engineering Professional Certificate
Intermediate 101 hours English Professional Certificate
Our recommendation
Microsoft's five-course path to building and shipping generative AI on Azure — prompt engineering, fine-tuning, deployment and MLOps, with responsible AI and security throughout. Most valuable if you're targeting Azure-based AI roles; it's opinionated toward Microsoft's ecosystem.
Skills you'll gain
Azure AIPrompt engineeringFine-tuning LLMsMLOpsModel deploymentResponsible AIMultimodal AI
Is this course right for you?
A good fit if you…
You're targeting Azure/Microsoft AI roles
You have Python and some ML familiarity
You want production, not just concepts
Consider something else if you…
You work outside the Azure ecosystem
You're new to programming or AI
You want vendor-neutral coverage
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.
What you'll learn
Build generative-AI applications on Microsoft Azure
Apply prompt engineering at a production level
Fine-tune large language models for specific tasks
Deploy and monitor models with MLOps practices
Integrate multimodal AI into applications
Apply responsible-AI, security and data-ethics principles
This course includes
101h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
Audit the courses free on Coursera; the professional certificate needs a paid Coursera subscription (around $49/month or Coursera Plus).
Comparison · LBS
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Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.
Is the certificate recognised?
Issued by Microsoft and hosted on Coursera. A strong signal for Azure-oriented AI roles; as always, employers weigh demonstrated skill and projects too.
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.
About this provider
CO
Coursera
University-backed online learning platform. 142M learners, 7,000+ courses from 325+ institutions.
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.