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Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) : AI-102日本語

AI-102日本語 actual test
  • Exam Code: AI-102J
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)
  • Updated: Aug 12, 2026
  • Q & A: 425 Questions and Answers
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About Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) : AI-102日本語 Exam

Microsoft AI-102日本語 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 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 3
  • Implement generative AI solutions: This domain focuses on building solutions with Microsoft Foundry and Azure OpenAI, including deploying models, implementing prompt flows and RAG patterns, generating content, and optimizing through parameter tuning and prompt engineering.
Topic 4
  • 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.

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

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AI-102: Designing and Implementing an Azure AI Solution Certification Path

The Microsoft Designing and Implementing an Azure AI Solution Certification includes only one AI-100 Exam.

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Topics Covered

Exam AI-102 contains five topics each of which is intended to check specific skills.

1. Plan and Manage an Azure Cognitive Services Solution

This topic implies your ability to choose the suitable Cognitive Services resource, create it, plan and design security for a Cognitive Services solution, and apply Cognitive Services containers. This means that you should be competent in selecting the appropriate cognitive service for solutions that refer to language analysis, speech, decision support, and vision. You also should possess skills to operate costs of Cognitive Services, create a Cognitive Services resource, and monitor a cognitive service. This part also checks how well you can operate Cognitive Services account keys, and protect Cognitive Services. Your knowledge of using Face API, Computer Vision, Speech, Text Analysis, and ability to integrate Cognitive Services Containers in Microsoft Azure will also be assessed.

2. Implement Computer Vision Solutions

The second topic is designed to check your skills in using the Computer Vision API to get image descriptions, define landmarks, find brands, edit content in images, and create thumbnails. In this part, you are expected to be able to detect faces and recognize them in images, analyze facial features, and match similar faces with the help of the Face API. Being competent in utilizing the Custom Vision service, you should demonstrate your skills in applying image classification and implementing an object detection solution. Besides, your ability to analyze video by implementing Azure Video Analyzer for Media will be measured.

3. Implement Natural Language Processing Solutions

In the third topic, candidates are required to show their skills in analyzing text by utilizing the Text Analytics service, control speech by implementing the Speech service, translate the text with the help of the Translator service. This domain also checks your proficiency in creating and optimizing an initial language model by utilizing LUIS, and finally, managing it.

4. Implement Knowledge Mining Solutions

In this domain, you will be required to have expertise related to applying a Cognitive Search solution, which implies creating data sources, identifying an index, running an indexer, and using synonyms. This topic also aims to evaluate your ability to apply an enrichment pipeline, use a knowledge store, operate a Cognitive Search solution and indexing.

5. Implement Conversational AI Solutions

This domain will evaluate your capacity in utilizing QnA Maker to make a knowledge base, creating and implementing conversation flow, creating a bot by utilizing either the Bot Framework Composer or the Bot Framework SDK. Finally, you will need to demonstrate your skills in integrating Cognitive Services into a bot.

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