Azure AI Fundamentals in London
Microsoft's entry-level AI certification covering machine learning, computer vision, NLP, and generative AI on Azure.
What is Azure AI Fundamentals?
The Azure AI Fundamentals certification (AI-900) is Microsoft's entry-level credential covering core AI and machine learning concepts on the Azure platform. It validates your understanding of AI workloads, responsible AI principles, and Azure's key cognitive services. In London, where financial services, tech scale-ups, and public sector organisations are accelerating AI adoption, this certification signals to employers that you can speak the language of AI projects — even in a non-technical role. Whether you're in data, consulting, product, or IT operations, the AI-900 gives you a credible foundation to participate in Azure-driven AI initiatives across one of Europe's most competitive job markets.
At $165 USD for the exam and zero prerequisites required, the AI-900 is one of the most accessible certifications with a measurable return. London's average IT salary sits around $85,000/yr, and certified professionals report an average uplift of $7,000/yr — that's roughly an 8% pay increase from a single beginner-level exam. London employers, particularly in fintech, consulting, and cloud services, actively filter for Microsoft credentials when hiring for AI-adjacent roles. With the certification renewing every two years, the ongoing investment is minimal compared to the earning potential. For anyone looking to break into AI or formalise existing knowledge, this is one of the clearest ROI decisions available in the London tech market right now.
Exam details
Prerequisites: None required
12-week study plan
Exam tips
Know the specific Azure service names for each AI category — examiners test whether you can match use cases to the correct service, such as Azure Form Recognizer for document extraction or Azure Bot Service for conversational AI.
Understand the difference between Azure Machine Learning and Azure Cognitive Services — many candidates confuse when to use a pre-built API versus when to train a custom model, and this distinction appears frequently in scenario-based questions.
Memorise the six Microsoft responsible AI principles — fairness, reliability, privacy, inclusiveness, transparency, and accountability — as these appear in both direct recall questions and applied scenario questions.
Practice identifying AI workload types from short scenario descriptions — the exam regularly presents a business problem and asks you to classify it as computer vision, NLP, conversational AI, anomaly detection, or knowledge mining.
Use the Azure free tier to actually interact with at least one Cognitive Services endpoint before your exam — even a brief hands-on session with the Language or Vision service helps you answer interface and capability questions with much greater confidence.