完璧-素晴らしいAI-901日本語版トレーリング試験-試験の準備方法AI-901模擬モード

AI-901試験は難しいです。だから、AI-901復習教材を買いました。本当に助かりました。先月、AI-901試験に参加しました。今日は、試験の結果をチエックし、嬉しいことに、AI-901試験に合格しました。AI-901復習教材は有効的な資料です。

Microsoft AI-901 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Identify AI concepts and responsibilities40-45%- Identify AI concepts and features
  • 1. Describe types of AI workloads
  • 2. Describe capabilities of machine learning
  • 3. Describe capabilities of computer vision
  • 4. Describe characteristics of generative AI
  • 5. Describe capabilities of natural language processing
- Describe principles of responsible AI
  • 1. Describe fairness considerations
  • 2. Describe inclusiveness considerations
  • 3. Describe reliability and safety considerations
  • 4. Describe transparency considerations
  • 5. Describe accountability considerations
  • 6. Describe privacy and security considerations
- Identify AI model components and configurations
  • 1. Describe model training and evaluation concepts
  • 2. Describe data preparation for AI models
  • 3. Describe model deployment and consumption concepts
Topic 2: Implement AI solutions by using Microsoft Foundry55-60%- Get started with Microsoft Foundry
  • 1. Navigate the Microsoft Foundry portal
  • 2. Create and configure a Foundry project
  • 3. Describe core features and use cases of Microsoft Foundry
- Implement AI solutions
  • 1. Monitor and manage AI solutions
  • 2. Use code examples to call AI services
  • 3. Integrate AI services into applications
  • 4. Implement single-agent solutions
- Work with models in Microsoft Foundry
  • 1. Evaluate model performance and safety
  • 2. Discover and deploy foundation models
  • 3. Customize models with prompt engineering
  • 4. Fine-tune models

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AI-901模擬モード & AI-901的中率

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Microsoft Azure AI Fundamentals 認定 AI-901 試験問題 (Q46-Q51):

質問 # 46
You are developing a lightweight application that will call an agent programmatically by using the Microsoft Foundry SDK.
You need to identify the agent ID.
What should you do?

正解:C

解説:
To determine the agent ID for calling an agent programmatically using the Microsoft Foundry SDK, the correct action is to in the Foundry playground, select Code, and view the .env variables (or look at the code view/overview section showing agent parameters like asst_ID).
When interacting with or testing an agent in the Foundry Playground, clicking the Code view reveals the pre-configured parameters, code snippets, and environment variables (such as the Assistant/Agent ID or project configurations) required to instantiate and call that exact agent programmatically through the SDK.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/code-interpreter


質問 # 47
You deploy the Azure OpenAI service to generate images.
You need to ensure that the service provides the highest level of protection against harmful content.
What should you do?

正解:D


質問 # 48
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:

Statement 1: Azure Content Understanding in Foundry Tools can analyze only PDF documents. = No Azure Content Understanding is not limited to PDF documents. It can analyze different content types, including documents, forms, images, audio, and video.
Statement 2: Azure Content Understanding in Foundry Tools results are returned in the JSON format.
= Yes
Azure Content Understanding returns structured analysis output in JSON format.
Statement 3: Azure Content Understanding in Foundry Tools can extract structured fields from documents and forms. = Yes Azure Content Understanding can extract structured fields from documents and forms by using analyzers and schemas.


質問 # 49
You are developing an application that analyzes invoices by using Azure Content Understanding in Foundry Tools.
You have a custom analyzer named invoiceAnalyzer.
You need to use the analyzer to process invoice files.
How should you complete the Python code? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:

The correct parameter is analyzer_id. The Azure AI Content Understanding Python SDK uses the ContentUnderstandingClient.begin_analyze() method to submit content for processing. Microsoft defines the method signature with analyzer_id as the required identifier that specifies which analyzer should process the supplied input.
Therefore, the code should be completed as:
poller = client.begin_analyze(analyzer_id= " invoiceAnalyzer " , ...)
A custom analyzer encapsulates the configuration that determines how Content Understanding interprets the source content and which fields or structured information it extracts. Because the analyzer has already been created with the name invoiceAnalyzer, that value is supplied through analyzer_id when the analysis operation begins.
extraction_type is not the parameter used to select an analyzer. model_name would refer conceptually to an underlying AI model, but Content Understanding analysis is invoked through an analyzer abstraction rather than by specifying a model directly. Likewise, schema_id does not identify the analyzer to execute.
Microsoft ' s custom-analyzer guidance explicitly demonstrates client.begin_analyze (analyzer_id=analyzer_id, inputs=[...]), confirming the required SDK pattern


質問 # 50
You are designing a system that will generate insurance quotes automatically.
Match the Microsoft responsible AI principles to the appropriate requirements.
To answer, drag the appropriate principle from the column on the left to its requirement on the right. Each principle may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.

正解:

解説:

Explanation:
Requirement
Principle
The decision-making process must be recorded so that staff can identify the reasoning behind a particular quote.
Transparency
A customer ' s personal information must be visible only to staff who are involved in the decision-making process.
Privacy and security
The system must be accessible to customers who use screen readers or other assistive technology.
Inclusiveness
Microsoft ' s Responsible AI framework defines six core principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability .
The first requirement maps to Transparency because personnel must be able to understand and review how the AI system arrived at an insurance quote. Transparency concerns making AI behavior, capabilities, limitations, and decision processes understandable. Recording the decision-making process provides the traceability required to explain a particular result.
The second requirement maps to Privacy and security . Restricting customer information to authorized staff directly implements least-privilege access and protects confidential personal data from unauthorized disclosure. Microsoft specifically associates this principle with respecting data boundaries and safeguarding information handled by AI systems.
The third requirement maps to Inclusiveness . AI systems should accommodate the full range of people they serve, including individuals who rely on assistive technologies. Support for screen readers and accessibility technologies ensures that users with disabilities are not excluded from interacting with the system. Microsoft explicitly connects inclusive AI design with accessibility considerations for people with disabilities.


質問 # 51
......

Microsoftさまざまな種類の候補者がAI-901認定を取得する方法を見つけるために、多くの研究が行われています。 シラバスの変更および理論と実践の最新の進展に応じて、AI-901テストトレントを修正および更新します。 AI-901認定トレーニングは、厳密な分析による近年のテストと業界動向に基づいています。 したがって、お客様のMicrosoft Azure AI Fundamentalsのために、より多くの選択肢が用意されています。試験のためにAI-901試験問題を選択することをお勧めします。

AI-901模擬モード: https://www.it-passports.com/AI-901.html