Purchase Microsoft : AI-103日本語 Exam Materials and then pass exam easily

Updated: Aug 08, 2026

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Microsoft AI-103日本語 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Developing AI Apps and Agents on Azure
Exam Number:AI-103
Exam Format:Multiple choice, Scenario-based, Case study, Performance-based items
Available Languages:English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil)
Exam Duration:100 minutes
Exam Price:$165 USD (varies by country/region)
Passing Score:700 / 1000
Related Certifications:Microsoft Certified: Azure AI Engineer Associate (retiring June 30, 2026)
Certificate Validity Period:1 year (renewable annually via free online assessment)
Real Exam Qty:50–60
Recommended Training:Microsoft Learn: Develop AI Apps and Agents on Azure
Azure AI Foundry Documentation
Exam Registration:Microsoft Certification Dashboard
Pearson VUE Registration
Sample Questions:Microsoft AI-103日本語 Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:No mandatory prerequisites; recommended experience: 6+ months building AI applications, proficiency in Python or C#, familiarity with Azure services and AI concepts
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-103

Microsoft AI-103日本語 Exam Syllabus Topics:

SectionWeightObjectives
Implement computer vision solutions10–15%- Build multimodal solutions
  • 1. Combine vision and language capabilities
  • 2. Process and analyze video content
- Implement image analysis and processing
  • 1. Implement object detection and image classification
  • 2. Use Azure AI Vision services
  • 3. Extract text and structure from images
Implement text and speech analysis solutions10–15%- Implement speech capabilities
  • 1. Speech-to-text and text-to-speech integration
  • 2. Speech translation and speaker recognition
- Implement natural language processing
  • 1. Build conversational language understanding
  • 2. Use Azure AI Language services
  • 3. Perform sentiment analysis, entity recognition, and summarization
Plan and manage Azure AI solutions25–30%- 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. Monitor and maintain AI workloads
  • 2. Configure model and agent deployments
  • 3. Integrate with CI/CD pipelines
Implement generative AI and agentic solutions30–35%- Design and implement intelligent agents
  • 1. Integrate agents with external systems and data sources
  • 2. Select agent architecture patterns
  • 3. Implement multi-agent workflows and orchestration
  • 4. Manage state, memory, and context
- Build generative AI applications
  • 1. Integrate Azure OpenAI and other models
  • 2. Build retrieval-augmented generation (RAG) solutions
  • 3. Implement prompt engineering and optimization
  • 4. Implement function calling and tool use
Implement information extraction and knowledge mining10–15%- Build knowledge bases and search solutions
  • 1. Create and manage vector indexes
  • 2. Implement Azure AI Search
  • 3. Design knowledge mining pipelines
- Extract structured data from documents
  • 1. Process forms, invoices, and unstructured content
  • 2. Use Azure AI Document Intelligence

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

1. ホットスポットに関する質問
Azure AI Search を使用するエンリッチメント パイプラインを作成しています。ナレッジ ストアには、構造化されていない JSON データと、スキャンされた PDF ドキュメントのテキストが含まれています。
各データタイプには、どの投影法を使用すべきでしょうか?回答するには、回答欄で適切なオプションを選択してください。
注:正解ごとに1ポイントが加算されます。


2. 2026年半ばに、Azure上で全く新しいエージェントアプリケーションの開発を開始し、Foundryエージェントの一般提供されサポートされているエントリーポイントを利用したいと考えています。どのAPIをターゲットにすべきでしょうか?

A) Foundry Agent Service を介したレスポンス API
B) LUISランタイムAPI
C) アシスタントAPI
D) 従来のテキスト補完API


3. あなたは、Project1 という名前の Microsoft Foundry プロジェクトにデプロイされたモデルを使用して応答を生成する App1 という名前の Web アプリケーションを構築しています。
App1は、モデルにプロンプ​​トを送信する前に、Azure AI Searchを使用してドキュメントを取得する必要があります。
Project1とApp1を統合する必要があります。ソリューションは以下の要件を満たす必要があります。
複数のクライアントアプリケーションは、同じ検索設定を使用する必要があります。
セキュリティポリシーは、鍵ベースの認証を防止するものでなければならない。
・管理業務の負担を最小限に抑える必要がある。
あなたはどうすべきでしょうか?

A) FoundryでカスタムHTTP接続を作成し、アプリケーションごとにAzure AI Searchエンドポイントを手動で構成します。
B) アプリケーションごとにマネージド ID を有効にし、Azure AI Search を直接呼び出します。
C) Project1でAzure AI Search接続を構成し、各アプリケーションでその接続を参照します。
D) Microsoft Entra認証を使用して、各アプリケーションからAzure AI Searchを直接呼び出します。


4. 注:このセクションには、同じシナリオと問題に関する複数の質問セットが含まれています。各質問には、問題に対する固有の解決策が提示されています。提示された解決策が、提示された目標を満たしているかどうかを判断する必要があります。セット内の複数の解決策が問題を解決できる場合もあります。また、セット内のどの解決策も問題を解決できない場合もあります。
このセクションの質問に回答すると、前のセクションに戻ることはできません。そのため、これらの質問は復習画面には表示されません。
画像のアップロードを受け付け、抽出した画像テキストを使用して応答を生成する、マルチモーダルなAI生成モデルをお持ちです。
ユーザーが安全でない画像をアップロードしたり、モデルを操作するための隠された指示を画像に埋め込んだりできることが分かります。
リスクを軽減するための対策を実施する必要があります。
解決策:保護対象物の検出設定を行います。
これは目標を達成していると言えるでしょうか?

A) いいえ
B) はい


5. マルチモーダルエージェントは、ユーザーがアップロードした画像を処理します。攻撃者は、エージェントがそれを読み取って実行することを期待して、画像内に隠しテキスト指示を埋め込みます。Azure AI Content Safety のどの機能が、このような攻撃を検出するように設計されていますか?

A) プロンプトシールドは、文書および間接的なプロンプト挿入を検出します。
B) 暴力カテゴリのコンテンツフィルタが「高」に設定されています
C) エージェントのファイル検索ツールを無効にする
D) アナライザーの画像解像度しきい値を上げる


Solutions:

Question # 1
Answer: Only visible for members
Question # 2
Answer: A
Question # 3
Answer: C
Question # 4
Answer: A
Question # 5
Answer: A

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