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 08, 2026
  • Q & A: 425 Questions and Answers

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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

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Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam

The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.

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Microsoft AI-102 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implement knowledge mining and information extraction solutions: This domain covers extracting structured data from unstructured sources using Azure AI Search, Document Intelligence for form processing, and Content Understanding for OCR and document analysis.
Topic 2
  • Implement natural language processing solutions: This domain involves text and speech processing, including sentiment analysis, translation, speech-to-text and text-to-speech implementation, building language understanding models, and creating question answering systems.
Topic 3
  • Implement an agentic solution: This domain covers creating autonomous AI agents using Microsoft Foundry Agent Service and Framework, implementing multi-agent workflows, and testing and deploying intelligent agents.
Topic 4
  • Implement computer vision solutions: This domain addresses image and video analysis using Azure Vision services, including object detection, text extraction, training custom vision models, and extracting insights from video streams.
Topic 5
  • Plan and manage an Azure AI solution: This domain covers selecting appropriate Azure AI services for various solution types, planning and deploying resources following Responsible AI principles, managing authentication and costs, and implementing content moderation and safety controls.

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

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