AI is everywhere now: in your inbox, your reports, your phone. Everyone uses it, but few people know what's happening under the hood. AI-901 gives you exactly that foundation — what AI actually is, what it can and can't do, and how you build it on Microsoft Azure. Not hype, but understanding you can actually use.
What you'll learn
The AI-901 exam (Azure AI Fundamentals) tests whether you understand the core concepts of AI and recognise how to apply them on Azure. From machine learning and computer vision to natural language and — since the refresh — generative AI with Azure AI Foundry.
In my training we don't treat those topics as loose buzzwords, but as one coherent picture. You learn not just what the building blocks are, but when which AI workload fits and why.
AI-901 — Official certification training (MCT)
This is an official AI-901 certification training for Microsoft Azure AI. We train according to the structure and learning objectives of Microsoft Learn, aligned with the AI-901 exam. As a Microsoft Certified Trainer (MCT) I combine that exam structure with your reality: where AI shows up in your work, the questions your team has, and what responsible use means in practice.
What Microsoft says you'll learn
- AI concepts and responsible AI: which types of AI workloads exist and what to watch for (fairness, reliability, transparency)
- The building blocks on Azure: machine learning, computer vision and natural language — what they do and when to use them
- Generative AI in practice: building solutions with Azure AI Foundry (language models, prompts, agents)
Who is this for?
- Professionals (technical and non-technical) who want to understand what AI on Azure really involves
- Teams getting started with AI who want a shared foundation and language
- Anyone who wants the AI-901 certificate with real understanding, not just exam facts
No programming experience required. Some familiarity with Python or cloud concepts is a plus, but not a prerequisite — we start from the concepts.
How this translates to my approach
We work with a recognisable example rather than abstract theory. Think of automatically reading or classifying documents, or a chat assistant on your own content. That's where you feel the difference between classic machine learning, a ready-made AI service and a generative model in Azure AI Foundry — and it becomes immediately clear where you use what.
Responsible AI runs through it as a common thread: what to watch for before you put something live, and how to explain why a model does what it does. Conceptual or hands-on—but always with a clear "this is how it fits together" line.
More about the setup on the way of working page. Curious who you'll be working with?
Want to know more? Get in touch.
Interested in AI-901?
Leave your name and email and tell me a bit about your situation. I'll get back to you personally to see what fits best.
Or explore: all training formats · way of working · contact page