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AI-103 試験練習問題

Microsoft Certified: Azure AI Apps and Agents Developer Associate

AI-103 の PDF 練習問題。資料の言語は 英語です。購入はこの試験のみで、自動更新はありません。

試験概要

AI-103 は「Microsoft Certified: Azure AI Apps and Agents Developer Associate」の認定試験です。試験形式、時間、対応言語は以下をご確認ください。最新の出題範囲や受験条件は公式サイトをご参照ください。

試験コード
AI-103
公式の試験・資格名
Microsoft Certified: Azure AI Apps and Agents Developer Associate
試験形式
Proctored assessment; interactive items may be included
試験時間
120 分
受験可能な言語
英語、簡体字中国語、繁体字中国語、フランス語、ドイツ語、日本語、韓国語、イタリア語、ポルトガル語(ブラジル)、スペイン語

公式試験の対応言語と練習問題ファイルの言語は異なります。試験の版と言語は公式の予約ページでご確認ください。

公式情報: 公式サイト
情報確認日:2026-10-20

対応言語

  • 英語
  • 簡体字中国語
  • 繁体字中国語
購入前にお試し

最初の 20 問を無料プレビュー

全 161 問

題庫の元の順序で表示します。回答欄を開くと、正解と収録されている解説を確認できます。

問題の言語:英語。問題文・選択肢・正解・解説は元の題庫の言語で表示します。

免責事項:ExamPico の問題はすべてインターネット上の情報を整理したもので、学習参考用として提供しています。

問題 11

Question#11Topic1

HOTSPOT -
You have a Microsoft Foundry project that contains an agent named PaymentAgent.
PaymentAgent includes a function tool that issues customer refunds by using an external API.
You are creating a workflow in YAML.
You need to ensure that the workflow pauses for human approval and continues with the refund step only after approval is granted.
How should you complete the workflow definition? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Question illustration

正解を表示

正解

AA

問題 12

Question#12Topic1

You have an Azure Speech in Foundry Tools resource that hosts a custom speech to text model deployed to a custom endpoint. An agent uses the endpoint to perform real-time speech recognition.
You are approaching the expiration date of the custom speech to text model.
What is the expected behavior when the model expires?

  1. A. Speech recognition requests will return a 4xx error until a new custom model is deployed.
  2. B. Speech recognition requests will continue to use the expired custom model until the model is removed manually.
  3. C. Speech recognition requests will fall back to the most recent base model for the same locale.
  4. D. The custom model will be deleted automatically when the model expires.
正解と解説を表示

正解

C

解説

Azure AI Search (Azure Cognitive Search) indexes PDF content from Azure Blob Storage using the Blob indexer and makes it available for retrieval. For grounding an agent on internal product PDF sheets, Azure AI Search provides indexing, enrichment (OCR), and semantic/vector retrieval for RAG scenarios. See: https://learn.microsoft.com/azure/search/search-howto-indexing-azure-blob-storage and https://learn.microsoft.com/azure/search/overview

問題 13

Question#13Topic1

You have a Microsoft Foundry project that contains a model deployment.
You have an application that calls the deployment by using the Azure OpenAI v1 API and DefaultAzureCredential.
The developers at your company receive HTTP 403 errors when they send inference requests, even after running az login.
You need to ensure that the developers can perform model inference. The solution must follow the principle of least privilege.
Which role-based access control (RBAC) role should you assign to the developers?

  1. A. Cognitive Services User
  2. B. Cognitive Services OpenAI User
  3. C. Contributor
  4. D. Cognitive Services Data Reader
正解と解説を表示

正解

C

解説

Azure AI Search (Azure Cognitive Search) indexes PDF content from Azure Blob Storage using the Blob indexer and makes it available for retrieval. For grounding an agent on internal product PDF sheets, Azure AI Search provides indexing, enrichment (OCR), and semantic/vector retrieval for RAG scenarios. See: https://learn.microsoft.com/azure/search/search-howto-indexing-azure-blob-storage and https://learn.microsoft.com/azure/search/overview

問題 14

Question#14Topic1

You have a Microsoft Foundry project that contains an agent. The agent has a Model Context Protocol (MCP) tool that queries a knowledge base stored in Azure AI Search.
Some agent runs return answers from the base model without invoking the knowledge base, which results in responses without grounded citations.
You are provided with the following code snippet that runs the agent.
Question illustration
You need to add the correct tool _choice parameter to the code to deterministically force the agent to invoke the MCP tool on each run.
What should you add?

  1. A. tool_choice={“required”}
  2. B. tool_choice={“auto”}
  3. C. tool_choice={“type”:“knowledge_base”}
  4. D. tool_choice ={“type”:“mcp”}
正解と解説を表示

正解

C

解説

Azure AI Search (Azure Cognitive Search) indexes PDF content from Azure Blob Storage using the Blob indexer and makes it available for retrieval. For grounding an agent on internal product PDF sheets, Azure AI Search provides indexing, enrichment (OCR), and semantic/vector retrieval for RAG scenarios. See: https://learn.microsoft.com/azure/search/search-howto-indexing-azure-blob-storage and https://learn.microsoft.com/azure/search/overview

問題 15

Question#15Topic1

DRAG DROP -
You have a Microsoft Foundry project that contains a customer support agent grounded in internal documentation.
After a recent update, users report the following issues:
Some answers are unsupported by retrieved documents.
A small number of responses are flagged for policy violations.
You need to evaluate each issue.
Which observability signals should you use for each issue? To answer, drag the appropriate observability signals to the correct issues. Each observability signal may be used once, more than once, or not at all. You may need to drag the spit bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Question illustration

正解を表示

正解

AC

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