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 19, 2026

Q & A: 425 Questions and Answers

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About Microsoft AI-102 Exam

Prep Options to Choose

The preparation process for the exam is a vital step on your way of passing the test, that’s why you need to find the most actual and reliable resources. Microsoft offers two options for you to choose from online free training or instructor-led, which is a paid one. For example, the free training represents a collection of learning paths each of which contains the different number of modules, from one to five. Thus, you can choose which ones to follow: Prepare for AI engineering (1 module), Process and Translate Speech with Azure Cognitive Speech Services (2 modules), Create computer vision solutions with Azure Cognitive Services (3 modules), to name a few. The paid course is known to be Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution and lasts for 4 days. It is intended for software developers interested in developing skills to build AI infused apps that use Azure Cognitive Search and Services, and Microsoft Bot Framework.

In addition, you can check the Amazon website to find the books on the topics included in the exam to ace it from the first attempt. Only after the successful passing the AI-102 exam you will earn the Microsoft Certified: Azure AI Engineer Associate certification. So, good luck!

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Languages: English, Japanese, Chinese (Simplified), Korean

Retirement date: none

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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What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam

  • Type of Questions: This test format is multiple choice.
  • Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
  • This is beta exam.
  • Length of Examination: 50 mins
  • Language: English, Japanese, Chinese (Simplified), Korean.
  • Passing Score: 700 / 1000

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

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

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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Implement generative AI solutions15-20%- Integrate Azure OpenAI and other generative models
- Deploy and manage generative models
- Implement model monitoring and feedback
- Orchestrate multiple models and containers
- Apply prompt engineering and fine-tuning
Implement computer vision solutions10-15%- Analyze images and detect objects/features
- Build and deploy custom vision models
- Process and index video content
- Integrate vision capabilities into applications
- Extract text and handwriting from images
Plan and manage an Azure AI solution20-25%- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Select appropriate Microsoft Foundry Services
- Select suitable AI models
- Create and configure Azure AI resources
- Plan solutions aligned with responsible AI principles
- Monitor, optimize, and secure AI solutions
Implement natural language processing solutions15-20%- Implement translation and summarization
- Build conversational AI and chatbots
- Customize and deploy NLP models
- Perform text analysis, sentiment detection, and language detection
Implement an agentic solution5-10%- Develop multi-agent workflows and orchestration
- Build agents with Microsoft Foundry Agent Service
- Test, deploy, and optimize agents
- Understand agent use cases and types
Implement knowledge mining and information extraction solutions15-20%- Build knowledge bases and search indexes
- Extract entities, relationships, and key phrases
- Ingest and process structured/unstructured data
- Implement intelligent search and retrieval

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