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

  • Exam Code: AI-102J
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)
  • Updated: Jul 27, 2026     Q & A: 425 Questions and Answers

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About Microsoft AI-102日本語 Exam

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

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Exam Details

Speaking of the exam details, the test will contain from 40 to 60 questions of various types which you need to complete within 100 or 120 minutes (depends on the inclusion of labs). To pass the exam you need to schedule the test on the PearsonVUE platform, pay an exam fee which is currently $165, and score at least 700 points or more out of 1000. And, of course, the knowledge of exam topics is a must.

How to Prepare For AI-102: Designing and Implementing an Azure AI Solution Exam

Preparation Guide for AI-102: Designing and Implementing an Azure AI Solution Exam

Introduction

Microsoft has created a track for Azure professionals analyze the requirements for AI solutions, recommend appropriate tools and technologies, and implements solutions that meet scalability and performance requirements, to get certified this platform. solution architects translate the vision and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions. The assessment is based on a rigorous exam using industry standard methodology to determine whether a candidate meets Microsoft's proficiency standards.

This certification been actually designed for aspirants design and implement AI apps and agents that use Microsoft Azure Cognitive Services.

For this exam candidate having proficiency in using cognitive service APIs to meet business requirements, appropriate AI models and services, automation requirements, data privacy and protection , bot state data , cognitive service output would be an added advantage.

Certification is evidence of your skills, expertise in those areas in which you like to work. If candidate wants to work as AI solution architect and prove his knowledge, certification offered by Microsoft. This AI-102 Exam Certification helps a candidate to validates his skills in Azure platform.

In this guide, we will cover the AI-102: Designing and Implementing an Azure AI Solution Certification exam, AI-102: Designing and Implementing an Azure AI Solution Certified professional salary and all aspects of the AI-102: Designing and Implementing an Azure AI Solution Certification.

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

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Microsoft AI-102日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement knowledge mining and information extraction solutions15-20%- Extract entities, relationships, and key phrases
- Build knowledge bases and search indexes
- Implement intelligent search and retrieval
- Ingest and process structured/unstructured data
Topic 2: Implement generative AI solutions15-20%- Orchestrate multiple models and containers
- Deploy and manage generative models
- Implement model monitoring and feedback
- Apply prompt engineering and fine-tuning
- Integrate Azure OpenAI and other generative models
Topic 3: Plan and manage an Azure AI solution20-25%- Select suitable AI models
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Plan solutions aligned with responsible AI principles
- Create and configure Azure AI resources
- Select appropriate Microsoft Foundry Services
- Monitor, optimize, and secure AI solutions
Topic 4: Implement an agentic solution5-10%- Understand agent use cases and types
- Develop multi-agent workflows and orchestration
- Test, deploy, and optimize agents
- Build agents with Microsoft Foundry Agent Service
Topic 5: Implement natural language processing solutions15-20%- Perform text analysis, sentiment detection, and language detection
- Customize and deploy NLP models
- Implement translation and summarization
- Build conversational AI and chatbots
Topic 6: Implement computer vision solutions10-15%- Build and deploy custom vision models
- Extract text and handwriting from images
- Analyze images and detect objects/features
- Process and index video content
- Integrate vision capabilities into applications

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