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.
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 for classification and detection, and configure speech recognition and synthesis workflows.
The exam also covers integration of multiple Azure AI services into one solution and evaluation of pipeline performance and reliability. The passing score is 700 out of 1000.
The exam is available in English, French, German, Spanish, and Italian. Abilene Academy's 3-day program covers all exam domains through hands-on labs led by active consultants, including real API-based architectures and SDK integration scenarios.
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 who prepare by memorizing service names consistently fail the integration scenario questions. AI-102 exam questions are case-based — they describe a business requirement and ask which combination of services, configurations, and architecture decisions solves it correctly. A candidate who knows that Azure AI Language exists but cannot explain when to use it instead of Azure OpenAI will miss the hardest tier of questions.
Well-prepared candidates have actually run code against each service family before exam day. They understand the behavioral limits of each service — latency, input constraints, error modes, and integration patterns — which is exactly what the scenario questions probe. That hands-on familiarity also makes the 3-day lab sessions productive from hour one rather than exploratory.
“Knowing what Azure AI Vision does is not the same as knowing when not to use it. The exam tests the second one.”
PECB ISO 27001 Senior Lead Auditor • ISO 27001 Lead Implementer
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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.
byRamzi AYNATI
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.
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More from AI-102: Designing and Implementing a Microsoft Azure AI Solution
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.
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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