Exam Code: AI-103
Exam Name: Developing AI Apps and Agents on Azure (AI-103日本語版)
Certification Provider: Microsoft
Corresponding Certification: Azure AI Engineer Associate

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Last Updated: Oct 05, 2026

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Microsoft AI-103日本語 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Implement computer vision solutions	10–15%	- Implement image analysis and processing 1. Extract text and structure from images 2. Use Azure AI Vision services 3. Implement object detection and image classification - Build multimodal solutions 1. Combine vision and language capabilities 2. Process and analyze video content
Topic 2: Implement text and speech analysis solutions	10–15%	- Implement speech capabilities 1. Speech translation and speaker recognition 2. Speech-to-text and text-to-speech integration - Implement natural language processing 1. Use Azure AI Language services 2. Perform sentiment analysis, entity recognition, and summarization 3. Build conversational language understanding
Topic 3: Implement generative AI and agentic solutions	30–35%	- Design and implement intelligent agents 1. Manage state, memory, and context 2. Integrate agents with external systems and data sources 3. Select agent architecture patterns 4. Implement multi-agent workflows and orchestration - Build generative AI applications 1. Integrate Azure OpenAI and other models 2. Build retrieval-augmented generation (RAG) solutions 3. Implement function calling and tool use 4. Implement prompt engineering and optimization
Topic 4: Plan and manage Azure AI solutions	25–30%	- Design Azure AI infrastructure 1. Plan for security, compliance, and responsible AI 2. Design for scalability, availability, and cost optimization 3. Select appropriate Azure AI Foundry services - Manage AI solution development lifecycle 1. Configure model and agent deployments 2. Monitor and maintain AI workloads 3. Integrate with CI/CD pipelines
Topic 5: Implement information extraction and knowledge mining	10–15%	- Build knowledge bases and search solutions 1. Implement Azure AI Search 2. Create and manage vector indexes 3. Design knowledge mining pipelines - Extract structured data from documents 1. Use Azure AI Document Intelligence 2. Process forms, invoices, and unstructured content

Microsoft Developing AI Apps and Agents on Azure (AI-103日本語版) Sample Questions:

Question #1

本番環境アプリケーションは、環境変数に格納された API キーを使用して Microsoft Foundry に対して認証を行います。セキュリティチームは、ハードコードされたシークレットを削除し、すべての呼び出しについてプリンシパルごとの監査を有効にするよう求めています。どちらのアプローチが両方の要件を満たしますか？

A. マネージドID(キーレス)を使用してMicrosoft Entra IDで認証する
B. サービス間で単一のAPIキーを共有し、IPアドレスの許可リストで制限する
C. APIキーをAzure Key Vaultに移動し、毎月ローテーションする
D. APIキーをマスク変数としてデプロイメントパイプラインに埋め込む

Reveal Solution Discussion 0

Correct Answer: A 🗳️