AI-103日本語 Exam Dumps

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Certification Provider:	Microsoft
Exam Code / Number:	AI-103-JPN
Exam Name:	Developing AI Apps and Agents on Azure (AI-103日本語版)
Exam Questions:	107
Last Updated:	Jul 24, 2026
Corresponding Certification:	Azure AI Engineer Associate

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Microsoft AI-103日本語 Exam Syllabus Topics:

Section	Weight	Objectives
Plan and manage Azure AI solutions	25–30%	- Manage AI solution development lifecycle 1. Configure model and agent deployments 2. Monitor and maintain AI workloads 3. Integrate with CI/CD pipelines - Design Azure AI infrastructure 1. Design for scalability, availability, and cost optimization 2. Plan for security, compliance, and responsible AI 3. Select appropriate Azure AI Foundry services
Implement generative AI and agentic solutions	30–35%	- Build generative AI applications 1. Implement function calling and tool use 2. Implement prompt engineering and optimization 3. Build retrieval-augmented generation (RAG) solutions 4. Integrate Azure OpenAI and other models - Design and implement intelligent agents 1. Integrate agents with external systems and data sources 2. Manage state, memory, and context 3. Select agent architecture patterns 4. Implement multi-agent workflows and orchestration
Implement information extraction and knowledge mining	10–15%	- Extract structured data from documents 1. Process forms, invoices, and unstructured content 2. Use Azure AI Document Intelligence - Build knowledge bases and search solutions 1. Implement Azure AI Search 2. Design knowledge mining pipelines 3. Create and manage vector indexes
Implement computer vision solutions	10–15%	- Build multimodal solutions 1. Combine vision and language capabilities 2. Process and analyze video content - Implement image analysis and processing 1. Use Azure AI Vision services 2. Extract text and structure from images 3. Implement object detection and image classification
Implement text and speech analysis solutions	10–15%	- Implement speech capabilities 1. Speech-to-text and text-to-speech integration 2. Speech translation and speaker recognition - Implement natural language processing 1. Perform sentiment analysis, entity recognition, and summarization 2. Build conversational language understanding 3. Use Azure AI Language services