Microsoft AI-102 : Designing and Implementing a Microsoft Azure AI Solution

  • Exam Code: AI-102
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution
  • Updated: Aug 30, 2026     Q & A: 425 Questions and Answers

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This exam measures your ability to accomplish the following technical tasks: plan and manage an Azure Cognitive Services solutions; implement Computer Vision solutions; implement natural language processing solutions; implement knowledge mining solutions; and implement conversational AI solutions.

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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102

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Following are some reference material for actual Microsoft AI-102 exam test

Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution

Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.

Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.

They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.

Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.

They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.

Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate

Download exam skills outline

Microsoft AI-102 Exam Syllabus Topics:

SectionObjectives
Topic 1: Implement Knowledge Mining and Document Intelligence- Implement document intelligence solutions
- Build Azure AI Search solutions
- Enrich and index data for search scenarios
Topic 2: Implement Generative AI Solutions- Integrate prompt engineering techniques
- Build retrieval-augmented generation (RAG) solutions
- Implement Azure OpenAI Service solutions
Topic 3: Implement Computer Vision Solutions- Extract information using OCR and form recognition
- Analyze images and videos using Azure AI Vision
- Implement custom vision models
Topic 4: Implement Natural Language Processing Solutions- Translate and interpret language using Azure AI services
- Analyze text using Azure AI Language
- Implement question answering and conversational AI
Topic 5: Plan and Manage an Azure AI Solution- Select appropriate Azure AI services
- Manage security, compliance, and responsible AI
- Plan solution requirements and architecture

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