AI-103試験問題はグローバルなものであるとMicrosoft誇らしく言えます。 したがって、どんな種類のAI-103テストトレントを求めても、当社のアフターサービスサービススタッフは、最も専門的な方法でAI-103練習問題の問題を解決するお手伝いをします。 AI-103のDeveloping AI Apps and Agents on Azure学習ツールを目指しているお客様は世界中のさまざまな国から来ており、間違いなく時間差があるため、AI-103トレーニングガイドで1日24時間、7日間、思いやりのあるMogiExamオンラインアフターサービスを提供します 週に数日、いつでもどこでも気軽にご連絡ください。
| Section | Weight | Objectives |
|---|---|---|
| Implement generative AI solutions | 25-30% | - Develop generative AI applications
|
| Plan and manage Azure AI solutions | 25-30% | - Plan Azure AI resources
|
| Implement agentic solutions | 20-25% | - Build AI agents
|
| Implement computer vision solutions | 10-15% | - Analyze visual content
|
| Implement text analysis and information extraction solutions | 10-15% | - Analyze and extract information
|
ご存知のように、AI-103証明書は、グローバル市場で非常に高い評価を得ており、大きな影響力を持っています。 しかし、Microsoft証明書を取得する方法は多くの人々にとって頭痛の種になりました。 AI-103学習教材はあなたに機会を提供します。 AI-103試験の実施を選択すると、あらゆる思いやりのあるサービスを提供できるように最善を尽くします。 当社の製品はお客様の観点から設計されており、採用した専門家が変化する傾向に応じてAI-103のDeveloping AI Apps and Agents on Azure学習教材を更新し、AI-103学習教材の高品質を確保します。
質問 # 36
You have an invoice-processing application named App1 that uses Azure Constant Understanding in Foundry Tools.
You are building a new Content Understanding pipeline named Pipeline1 that must meet the following requirements:
- Compare an invoice to its related purchase order
- Validate the voice against static vendor contact documents
- Return a single structured output that includes discrepancy findings
You need to configure Pipeline1 and expose the pipeline as a single analyzer endpoint. What should you configure?
正解：B
解説：
Multiple-file task: Required over a single-file task. Your pipeline needs to reconcile data across two separate active transactional documents (the invoice and the purchase order) within a single analyzer request.
Pro mode is required instead of standard mode. Pro mode is specifically designed for advanced scenarios requiring multi-step reasoning, cross-file analysis, and validation against a knowledge base. Note that Pro mode currently supports classify and generate fields but does not support confidence scores for specific extracted fields.
Vendor contract files as reference data: Required. Because the vendor contracts are static compliance documents, they should be uploaded and treated as the analyzer's background knowledge base (reference data) to guide the validation logic.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/standard-pro-modes
質問 # 37
Hotspot Question
You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:
- Use a single key and endpoint to access multiple services.
- Consolidate billing for future services that you might use.
- Support the use of Azure Vision in Foundry Tools in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Box 1: PUT
Need to create a Cognitive Services Multi-Service resource using the PUT method. This specific resource type provides a single endpoint and key for multiple AI services, consolidates billing, and supports Azure Vision.
Box 2: CognitiveServices
Using the CognitiveServices kind creates a multi-service resource. This fulfills all the requirements by providing a single key and endpoint for multiple services, consolidating billing, and enabling access to features like Azure AI Vision and Text Analytics under one roof.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/sdk-overview
質問 # 38
You have a Microsoft Foundry project that contains an agent.
You need to enable long-term memory to ensure that the agent can recall user preferences across separate conversations. Stored memories must be isolated per authenticated user without the client application manually generating user IDs.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets.
Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
scope = " {{userId}} "
tools = [memory_tool]
The correct scope value is {{userId}} because the requirement is per-authenticated-user memory isolation without the client application manually generating user identifiers. In Microsoft Foundry Agent Service memory, the scope parameter partitions memory items inside the memory store. The official guidance states that when the memory search tool is attached to an agent, setting scope to the user identity template enables per-user memory isolation; the service resolves the end-user identity from the request header when provided, or falls back to the Microsoft Entra tenant ID and object ID of the caller. This matches the requirement to isolate stored preferences by authenticated user automatically.
The tools property must be [memory_tool] because the MemorySearchTool instance is created earlier and must be attached to the PromptAgentDefinition. Foundry guidance shows the memory search tool being passed in the agent definition as tools=[tool] , allowing the agent to read from and write to the configured memory store during conversations.
" session " and {{conversationId}} would limit continuity to a session or conversation instead of enabling long-term recall across separate conversations. [mem_store_name] is a list containing the store name, not a tool definition. Reference topics: Foundry Agent Service memory, memory stores, memory search tools, scope, and per-user isolation.
質問 # 39
You plan to deploy a containerized version of an Azure Al Language service that will be used for sentiment analysis.
You configure https: //contoso.cognitiveservices.azure, cow as the endpoint URI for the service.
You need to run the container on an Azure virtual machine by using Docker.
How should you complete the command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
First selection:
mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment
Second selection:
https://contoso.cognitiveservices.azure.com
Completed command:
docker run --rm -it -p 5000:5000 --memory 8g --cpus 1 \
mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment \
Eula=accept \
Billing=https://contoso.cognitiveservices.azure.com \
ApiKey=xxx
The image mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment is the official Microsoft Container Registry image for Azure AI Language sentiment analysis. The Billing argument must reference the endpoint of the provisioned Azure AI Language resource associated with the supplied API key. It is not the address used by applications to invoke the locally running container.
Azure
AI containers require three licensing and metering parameters: Eula=accept, a valid Billing endpoint, and ApiKey. Without all three values, the container does not start. The command maps host port 5000 to container port 5000, allocates 8 GB of memory and one CPU, creates an interactive terminal, and automatically removes the stopped container. Applications subsequently invoke the locally hosted service through an address such as http://
< vm-address > :5000. The Azure endpoint remains responsible for metering and authentication; analyzed customer text is processed by the container rather than sent to the billing endpoint.
Study Guide alignment: Implement text analysis solutions - perform sentiment analysis and opinion mining, deploy Azure Language containers, and configure container billing parameters.
質問 # 40
Hotspot Question
You have a Microsoft Foundry project that contains a customer support agent built by using the Foundry Agent Service.
The agent uploads user-provided screenshots to Azure Storage through a ticketing tool and receives a blob URL for additional reasoning.
You need to use image moderation during agent runs and prevent harmful content from being returned during runs. Azure AI Content Safety must access the images by using the blob URL.
The solution must follow the principle of least privilege.
What should you configure for Content Safety? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
質問 # 41
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