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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
Topic 2
  • Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.

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Microsoft Azure AI Fundamentals Sample Questions (Q40-Q45):

NEW QUESTION # 40
You need to create an AI agent in Microsoft Foundry that follows a specific role and behavior when responding to users. What should you configure?

Answer: B

Explanation:
To create an AI agent that follows a specific role and behavior, you configure system instructions.
Microsoft Foundry Agent Service documentation states that agent instructions define goals, constraints, and behavior.


NEW QUESTION # 41
You are developing an application that uses the Azure Language SDK and a Microsoft Foundry resource.
You need to return a list of important topics from unstructured text.
Which Python method should you use?

Answer: C

Explanation:
To return important topics from unstructured text by using Azure Language SDK, use:
client.extract_key_phrases()
Microsoft states that key phrase extraction evaluates unstructured text and returns a list of key phrases or main topics. The Azure Text Analytics client library for Python includes the extract_key_phrases method for this task.
Why the other options are incorrect:
A). client.recognize_linked_entities() identifies entities and links them to a knowledge base.
B). client.recognize_entities() identifies named entities such as people, organizations, locations, dates, and quantities.
C). client.begin_extract_summary() starts an extractive summarization operation, not key phrase extraction.


NEW QUESTION # 42
Drag and Drop Question
You have a Microsoft Foundry project that contains a model deployment.
You are developing an application that sends an image and a user question to the model.
You need to send both text and image content in the same request so the model can return an answer.
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. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 43
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.

Answer:

Explanation:

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.


NEW QUESTION # 44
Drag and Drop Question
You have a Microsoft Foundry project that contains a model deployment.
You are developing an application that sends an image and a user question to the model.
You need to send both text and image content in the same request so the model can return an answer.
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. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 45
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