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

AI-102日本語 Exam Simulator
  • Exam Code: AI-102J
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)
  • Updated: Jul 24, 2026
  • Q & A: 425 Questions and Answers

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Introduction to AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates for AI-102 Exam are seeking to prove fundamental knowledge and skills in Designing and Implementing an Azure AI Solution domain. Before taking this exam, aspirants ought to have a solid fundamental information of the concepts shared in preparation guide as well as basic understanding of Azure administration, Azure development, and DevOpss would give an added edge.

This exam validates the ability to use the various services within the Microsoft Azure Artificial Intelligence (AI) portfolio.

It is suggested that professionals accustomed to the ideas and also the technologies represented here by taking relevant training courses. Candidates are expected to have some hands-on experience on bot services that use Language Understanding , bots with Azure Application Insights, creating a GPU, FPGA, or CPU-based solution, implementing AI workflow.

After passing this exam, candidates get a certificate from Microsoft that helps them to demonstrate their proficiency to their clients and employers.

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

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