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

AI-102日本語 pass collection

Exam Code: AI-102J

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

Updated: Jul 26, 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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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.

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

For more info read reference:

microsoft learning site AI-102 Skills measured Publish a Machine Learning Experiment with Microsoft Azure Machine Learning Studio Process and translate speech with Azure Cognitive Speech Services

Microsoft AI-102日本語 Exam Syllabus Topics:

SectionWeightObjectives
Implement Decision Support Solutions10-15%- Integrate Azure AI services into applications
- Monitor and optimize decision support solutions
- Design and implement decision automation
Plan and Manage an Azure AI Solution15-20%- Implement governance and compliance for AI solutions
- Plan and configure secure AI solutions
- Select appropriate Azure AI services and technologies
- Manage AI costs and resource allocation
Implement Computer Vision Solutions15-20%- Process video and generate insights
- Implement object detection and image classification
- Analyze images using Azure AI Vision
- Read and process documents using Azure AI Document Intelligence
- Implement Azure AI Face service
Implement Natural Language Processing Solutions20-25%- Create conversational AI solutions with Azure AI Bot Service
- Analyze text using Azure AI Language
- Translate text and speech
- Implement speech capabilities using Azure AI Speech
- Build question answering solutions
Implement Knowledge Mining and Document Intelligence Solutions15-20%- Implement semantic and vector search
- Design document processing pipelines
- Implement Azure AI Search solutions
- Create custom skills for Azure AI Search
Implement Generative AI Solutions10-15%- Implement prompt engineering techniques
- Integrate Azure OpenAI models into applications
- Apply responsible AI practices
- Use Azure OpenAI Service for generative AI

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