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Microsoft AI-103日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Extract text and structure from images
  • 2. Use Azure AI Vision services
  • 3. Implement object detection and image classification
Topic 2: Implement information extraction and knowledge mining10–15%- Extract structured data from documents
  • 1. Use Azure AI Document Intelligence
  • 2. Process forms, invoices, and unstructured content
- Build knowledge bases and search solutions
  • 1. Design knowledge mining pipelines
  • 2. Create and manage vector indexes
  • 3. Implement Azure AI Search
Topic 3: Implement text and speech analysis solutions10–15%- Implement natural language processing
  • 1. Use Azure AI Language services
  • 2. Perform sentiment analysis, entity recognition, and summarization
  • 3. Build conversational language understanding
- Implement speech capabilities
  • 1. Speech translation and speaker recognition
  • 2. Speech-to-text and text-to-speech integration
Topic 4: Plan and manage Azure AI solutions25–30%- Design Azure AI infrastructure
  • 1. Select appropriate Azure AI Foundry services
  • 2. Design for scalability, availability, and cost optimization
  • 3. Plan for security, compliance, and responsible AI
- Manage AI solution development lifecycle
  • 1. Integrate with CI/CD pipelines
  • 2. Monitor and maintain AI workloads
  • 3. Configure model and agent deployments
Topic 5: Implement generative AI and agentic solutions30–35%- 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
- Design and implement intelligent agents
  • 1. Implement multi-agent workflows and orchestration
  • 2. Manage state, memory, and context
  • 3. Integrate agents with external systems and data sources
  • 4. Select agent architecture patterns

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
貴社は、Microsoft Foundryプロジェクト「Project1」において、顧客サポートエージェントの試験運用を行っています。
Project1は既存のApplication Insightsリソースに接続されており、同社のサポートチームは「トレース」タブで実行結果を確認します。
Foundryエージェントサービスは、以下の動作を実行するように構成されています。
- Application Insights の接続文字列を取得するには、次の関数を呼び出します。
project_client.telemetry.get_application_insights_connection_string()。
- configure_azure_monitor(connection_string=...) を呼び出して有効化します
テレメトリー。
別のLangChainサービスがOpenTelemetryを使用するように構成されており、以下の設定になっています。
- AzureAIOpenTelemetryTracer(connection_string=...,
enable_content_recording=False)
- config={"callbacks":[azure_tracer]} を使用してトレーサーを渡します。
会社の方針には以下の要件があります。
- LangChainとOpenTelemetryからのテレメトリは区別可能である必要がある
同じ Application Insights リソース内。
- プロンプトやツールに秘密情報や認証情報を保存してはいけません
引数、またはスパン属性。
以下の各記述について、正しい場合は「はい」を選択してください。そうでない場合は「いいえ」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. 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) 音声ストリームに対するAzure AI Document Intelligence
B) Azure Translatorを使用して音声を変換します
C) 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
D) デフォルトのテキスト読み上げ音声のみ


3. Microsoft Foundry プロジェクトがあり、その中に Foundry Agent Service を使用して構築されたサポート チケットのトリアージ エージェントが含まれています。
エージェントはツールを使用してチケットの種類を分類し、チケットの優先度を設定します。
場合によっては、同じサポート案件が数日間にわたる複数のセッションにまたがって継続されることがあります。
エージェントが完全なインタラクション履歴を自動的に再利用できるように、永続的なIDを使用して状態を保持する必要があります。ソリューションは、ターンやセッションをまたいで、以前のユーザーメッセージ、ツール呼び出し、ツール出力を保持しなければなりません。
どのランタイムコンポーネントを使用すべきですか?

A) 出力項目
B) エージェント
C) 会話
D) 応答


4. あなたはMicrosoft Foundryプロジェクトを持っています。
社内ポリシー文書の検索ソリューションをサポートするには、モデルカタログからモデルをデプロイする必要があります。このモデルは、文書内のテキストとユーザーのクエリのベクトル表現を生成する必要があります。
どのタイプのモデルを使用すべきですか?

A) 小型言語モデル(SLM)
B) 埋め込みモデル
C) 画像生成モデル
D) 大規模言語モデル(LLM)


5. あなたは、GPTリアルタイムモデルを使用するApp1という名前の顧客サポートWebアプリをMicrosoft Foundryで構築しています。
アプリ1は以下をサポートする必要があります:
- Azure OpenAI を使用した、リアルタイムで低遅延の音声会話
- ユーザーからのストリーミング音声入力と再生音声応答
クライアントアプリケーションでリアルタイムオーディオストリーミングをサポートし、レイテンシが約100ミリ秒を目標とする接続方法を設定する必要があります。
どの接続方法を使用すべきですか?

A) WebSocket
B) RTMP
C) SIP
D) WebRTC


Solutions:

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

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