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Microsoft AI-103日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Plan and manage Azure AI solutions25–30%- Manage AI solution development lifecycle
  • 1. Integrate with CI/CD pipelines
  • 2. Monitor and maintain AI workloads
  • 3. Configure model and agent deployments
- Design Azure AI infrastructure
  • 1. Select appropriate Azure AI Foundry services
  • 2. Plan for security, compliance, and responsible AI
  • 3. Design for scalability, availability, and cost optimization
Topic 2: Implement information extraction and knowledge mining10–15%- 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. Process forms, invoices, and unstructured content
  • 2. Use Azure AI Document Intelligence
Topic 3: Implement generative AI and agentic solutions30–35%- Build generative AI applications
  • 1. Integrate Azure OpenAI and other models
  • 2. Implement prompt engineering and optimization
  • 3. Build retrieval-augmented generation (RAG) solutions
  • 4. Implement function calling and tool use
- Design and implement intelligent agents
  • 1. Integrate agents with external systems and data sources
  • 2. Implement multi-agent workflows and orchestration
  • 3. Manage state, memory, and context
  • 4. Select agent architecture patterns
Topic 4: Implement text and speech analysis solutions10–15%- Implement speech capabilities
  • 1. Speech translation and speaker recognition
  • 2. Speech-to-text and text-to-speech integration
- Implement natural language processing
  • 1. Perform sentiment analysis, entity recognition, and summarization
  • 2. Use Azure AI Language services
  • 3. Build conversational language understanding
Topic 5: Implement computer vision solutions10–15%- Build multimodal solutions
  • 1. Process and analyze video content
  • 2. Combine vision and language capabilities
- 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

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

Question 1

ドラッグアンドドロップ問題
デプロイ済みのチケットトリアージエージェントを含むMicrosoft Foundryプロジェクトがあります。
エージェントがツールを必要とする場合でも、ツールを呼び出さずに応答することがあるということに気づくでしょう。
エージェントが実行中にツールを呼び出すようにする必要があります。
Pythonコードを完成させるにはどうすればよいでしょうか?適切な値を正しいターゲットにドラッグして答えてください。各値は1回、複数回、または全く使用されない場合があります。コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要がある場合があります。
注:正解ごとに1ポイントが加算されます。


Question 2

ホットスポットに関する質問
あなたは、顧客からのコメントを収集し、公開フォーラムに投稿するPythonアプリケーションを持っています。
Azure AI Content Safetyにテキストコメントを送信し、応答から自傷行為の深刻度を返す必要があります。
コードをどのように完成させればよいでしょうか?回答するには、回答欄で適切な選択肢を選んでください。
注:正解ごとに1ポイントが加算されます。


Question 3

あなたは薬局向けの音声エージェントを開発しています。音声による質問を受け付け、合成音声で応答し、一般的な音声モデルでは聞き間違えやすい専門的な医薬品名を正確に認識する必要があります。どの機能を構成すべきでしょうか?

A. エージェント内の音声テキスト変換のためのカスタム音声モデル
B. 音声ストリームに対するAzure AI Document Intelligence
C. Azure Translatorを使用して音声を変換します
D. デフォルトのテキスト読み上げ音声のみ


Question 4

ホットスポットに関する質問
顧客サポートのトリアージプロセス用のワークフローを含むMicrosoft Foundryプロジェクトがあります。
質問ノードがあり、ユーザーの回答はVar01という名前のローカル変数に保存されます。
以下のPower Fx式を作成する必要があります。
- Var01 に以下の内容が含まれることを保証する if/else 条件式
価値
- 保存されたユーザー応答を返す送信メッセージ式
大文字
式はどのように設定すればよいですか?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。


Question 5

Azure Blob Storageに保存されている請求書を取り込む、Pipeline1という名前のAzure AI Searchインデックス作成パイプラインを構築しています。請求書はスキャンされた画像として保存されています。
ユーザーが請求書の各項目を横断して請求書データを検索できるようにする必要があります。
Pipeline1のスキルセットに、どの組み込みスキルを追加すべきでしょうか?

A. 光学文字認識(OCR)
B. テキスト分割
C. 画像解析
D. テキスト翻訳


Solutions:

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

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