What is the Microsoft AI-102 certification and what does it qualify you to do?
The AI-102 exam leads to the Microsoft Certified: Azure AI Engineer Associate credential, which validates the ability to design and implement AI solutions using Azure AI services. Certified engineers can build document intelligence pipelines, deploy conversational agents with multi-turn logic, configure computer vision models, and integrate speech and translation workflows via REST APIs and SDKs.
The AI-102 exam leads to the Microsoft Certified: Azure AI Engineer Associate credential, which validates the ability to design and implement AI solutions using Azure AI services. Certified engineers can build document intelligence pipelines, deploy conversational agents with multi-turn logic, configure computer vision models, and integrate speech and translation workflows via REST APIs and SDKs.
The certification is recognized across cloud and enterprise AI roles, and covers Azure AI Foundry, Azure AI Language, Azure AI Vision, Azure AI Document Intelligence, and Azure AI Speech as an integrated set of services.
For professionals building production AI systems on Azure, AI-102 is the primary technical credential. The passing score is 700 and the exam is available in English, French, German, Spanish, and Italian.
Related Information
- Exam AI-102 · Passing score: 700/1000
- Standard Microsoft exam format · Available in EN, FR, DE, ES, IT · CHF 119 in Switzerland
- Microsoft certification · No expiry — stays current with Azure AI product updates
- Recommended path: AZ-900 or AI-900 → AI-102 with active Python/REST experience
- 3-day instructor-led program at Abilene Academy · Hands-on labs with Azure AI Foundry throughout
Expert Insight
Candidates coming from a pure cloud architecture background without hands-on API development consistently underestimate the engineering depth. They expect a service catalog overview — but the labs immediately require calling Azure AI services via code, handling errors, and integrating multiple modalities. The conceptual gap becomes obvious on day one, not day three.
Well-prepared candidates treat the first lab as a validation of existing skills, not a learning exercise. They have already called an Azure SDK or REST endpoint before day one, and they use the course to understand how services interact at an architectural level — which is exactly what the exam scenario questions test at the hardest difficulty tier.
“AI-102 is not a conceptual certification. It's an engineering certification that happens to be about AI.”
PECB ISO 27001 Senior Lead Auditor • ISO 27001 Lead Implementer
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View courseRelated Answers
What does the AI-102 exam cover?
The AI-102 exam tests the ability to build AI applications using Azure AI Foundry, develop conversational agents with Azure AI Language, implement document data extraction pipelines, deploy computer vision models, and configure speech recognition and synthesis workflows. The passing score is 700 out of 1000.
byGerhard ROTTER
What are the prerequisites for AI-102 training?
AI-102 requires practical experience with Python or C#, familiarity with REST APIs and SDKs, and a working understanding of cloud concepts and JSON. Without these foundations, participants will struggle with service integration exercises and lab completion.
byJean MUNYARUGERERO
Who should attend AI-102 training?
AI-102 training is designed for software developers building cloud-based AI applications, AI engineers integrating Azure cognitive services, and backend developers handling language, vision, or document processing in a single system. Technical consultants who need to justify AI architecture decisions to stakeholders also benefit.
byJean MUNYARUGERERO
More from AI-102: Designing and Implementing a Microsoft Azure AI Solution
What does the AI-102 exam cover?
The AI-102 exam tests the ability to build AI applications using Azure AI Foundry, develop conversational agents with Azure AI Language, implement document data extraction pipelines, deploy computer vision models, and configure speech recognition and synthesis workflows. The passing score is 700 out of 1000.
What are the prerequisites for AI-102 training?
AI-102 requires practical experience with Python or C#, familiarity with REST APIs and SDKs, and a working understanding of cloud concepts and JSON. Without these foundations, participants will struggle with service integration exercises and lab completion.
Who should attend AI-102 training?
AI-102 training is designed for software developers building cloud-based AI applications, AI engineers integrating Azure cognitive services, and backend developers handling language, vision, or document processing in a single system. Technical consultants who need to justify AI architecture decisions to stakeholders also benefit.
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