Microsoft AB-100模擬試験 & AB-100問題数

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効果的なAB-100模擬試験 & 合格スムーズAB-100問題数 | 有難いAB-100関連日本語内容

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Microsoft AB-100 認定試験の出題範囲:

トピック出題範囲
トピック 1
  • AIを活用したビジネスソリューションの設計:Copilot Studio、Microsoft Foundry、Dynamics 365などのプラットフォームを使用して、AIエージェント、Copilot統合、インテリジェントワークフローを設計する方法を解説します。プランニングプロンプト、コネクタ、エージェントの動作、ソリューションの拡張性についても説明します。
トピック 2
  • AIを活用したビジネスソリューションの導入:本番環境におけるAIソリューションの導入、テスト、監視、最適化に重点を置きます。また、ALMプロセスの管理、パフォーマンス監視、セキュリティ、ガバナンス、責任あるAIコンプライアンスの確保も含まれます。
トピック 3
  • AIを活用したビジネスソリューションの計画:ビジネス要件の分析と、AIエージェントや生成型AIがプロセスを改善できる箇所の特定に重点を置きます。また、AI戦略の策定、投資対効果(ROI)の評価、AIコンポーネントの構築、購入、拡張の決定も含まれます。

Microsoft Agentic AI Business Solutions Architect 認定 AB-100 試験問題 (Q31-Q36):

質問 # 31
A company plans to deploy a Microsoft Copilot Studio agent that will analyze historical business data to predict customer behavior.
The data is currently stored in an Azure SQL database, flat files, APIs, and logs.
You need to organize the data into a format that can be used as a knowledge source in Copilot Studio.
What should you include in the solution?

正解:B

解説:
Microsoft Copilot Studio agents can analyze customer behavior by leveraging business data from Azure SQL, files, and APIs by using Azure AI Search as a knowledge source. By importing and vectorizing this structured and unstructured data into an Azure AI Search index, the agent can perform semantic, meaning-based searches to retrieve context-relevant information.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-azure-ai-search


質問 # 32
A company has a Microsoft Copilot Studio agent that provides answers based on a knowledge base for customer support.
Users report that, occasionally, the agent provides inaccurate answers.
You need to use metrics from the Analytics tab in Copilot Studio to identify the cause of the inaccuracies.
Which two options should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

正解:A、C

解説:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answers are B. session information and session outcomes and E. quality of generated answers .
This scenario is focused on a knowledge base-driven Copilot Studio agent where users report that the agent sometimes gives inaccurate answers . The question asks which Analytics tab metrics should be used to identify the cause of those inaccuracies.
That means you need metrics that help you examine:
* how the answer was generated
* what happened in the conversation when the bad answer occurred
Why E. quality of generated answers is correct
This is the most direct metric for this scenario.
Because the agent is answering from a knowledge base , the problem is tied to the quality of the generated response itself. The quality of generated answers metric helps assess whether the generated responses are relevant, useful, and accurate enough for the user's request.
From an AI business solutions perspective, this metric is essential because it helps diagnose problems such as:
* weak grounding from the knowledge source
* irrelevant retrieval
* poor answer formulation
* hallucination-like behavior
* mismatch between user question and available source content
If the issue is inaccurate answers, the first place to investigate is the quality signal tied to generated answers.
Why B. session information and session outcomes is correct
To find the cause of inaccuracies, you also need to inspect the broader conversational context. Session information and session outcomes help you see:
* what the user asked
* how the agent responded
* whether the conversation was resolved
* whether the user abandoned, escalated, or retried
* where the conversation broke down
This is important because an inaccurate answer may not come only from poor generation quality. It may also come from:
* the way the user phrased the request
* lack of sufficient grounding context
* repeated failed attempts in a session
* escalation after an unhelpful answer
* patterns in unsuccessful conversations
In other words, quality of generated answers tells you about answer quality, while session information and outcomes help you understand the operational context in which those inaccuracies appear.
Together, these two give the strongest diagnostic view.
Why the other options are incorrect
A). survey results
Survey results can tell you whether users were happy or unhappy, but they do not directly help identify the cause of inaccurate knowledge-based responses. They are more of a feedback signal than a root-cause metric.
C). topic usage and topics with low resolution
This is more relevant for agents built around explicit topics and topic flows. The scenario specifically describes an agent that provides answers based on a knowledge base , so generated-answer analytics are more appropriate than topic-resolution analysis.
D). engagement, resolution, and escalation rates
These are useful high-level operational KPIs, but they are not the best metrics for diagnosing why answers are inaccurate. They show outcome trends, not the direct cause of answer-quality issues.


質問 # 33
A company has a Microsoft Copilot Studio agent for customer support. You are reviewing and validating the following prompts:
* A prompt that has instructions to " help the customer as best you can "
* A prompt that helps retrieve product information from a knowledge base You need to ensure that the agent delivers consistent and accurate responses.
What should you do for each prompt? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:

This question is about improving prompt quality so a Microsoft Copilot Studio agent gives consistent and accurate answers.
For the first prompt, "help the customer as best you can" is too vague. It does not tell the model exactly what task to perform, what boundaries to follow, or what kind of response is expected. The correct improvemen t is to rewrite the prompt with clear and task-specific instructions . Clear prompts reduce ambiguity and make agent behavior more predictable and repeatable.
For the second prompt, the agent is retrieving product information from a knowledge base . To keep answers accurate and grounded, the best practice is to use responses with only reference sources and limit the response scope . That ensures the model stays tied to approved knowledge and does not invent unsupported product details.
Why the other options are not correct:
* Add filler words to make the prompt sound more natural and conversational does not improve accuracy or consistency.
* Keep the prompt vague to enable model flexibility increases inconsistency.
* Add several open-ended questions to give the model broader context can make responses less focused.
* Remove the knowledge source so that the model responds freely with general product information would reduce reliability and increase hallucination risk.


質問 # 34
You are designing a low-code Al business solution by using Microsoft Copilot Studio.
The solution must include an agent that automates tasks by simulating user interactions across third-party apps and websites, such as clicking buttons, entering text, and extracting information from screens.
You need to recommend what to include in the agent.
What should you recommend?

正解:A

解説:
" Computer use is a tool in Copilot Studio that lets your agent interact with and automate tasks on a Windows computer. It works with websites and desktop apps by selecting buttons, choosing menus, and entering text into fields on the screen. Describe in natural language what you want computer use to do, and it performs the task on a computer you set up by using a virtual mouse and keyboard. By using computer use, agents can complete tasks even when there ' s no API to connect directly to the system. If a person can use an app or website, computer use can too. You can use computer use for tasks like automated data entry, invoice processing, and data extraction. " Reference: https://learn.microsoft.com/en-us/microsoft-copilot-studio
/computer-use


質問 # 35
A company has an Azure environment that supports multiple business units.
The company plans to implement an Al solution that will perform sentiment analysis on customer product reviews. You need to evaluate the potential cost of the solution to support return on Al investment (ROAI) analysis. What should you use?

正解:D


質問 # 36
......

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