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Microsoft AI-901 Exam Syllabus Topics:

Topic	Details
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?

A. temperature
B. max completion tokens
C. system instructions
D. tokens per minute (TPM)

Answer: C

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.
Option A. tokens per minute (TPM) controls throughput quota, not behavior.
Option C. temperature controls response randomness/creativity, not the agent's role.
Option D. max completion tokens controls response length, not the agent's role or behavioral rules.
Therefore, the correct answer is B. system instructions.

NEW QUESTION # 41
You are developing an application that extracts fields from PDFs by using Azure Content Understanding in Foundry Tools.
You need to use the Python SDK to submit a PDF for analysis and retrieve the extraction results.
What should you do?

A. Use optical character recognition (OCR) to extract text from the PDF and map the fields in the code.
B. Call analyze() to return the extracted fields synchronously in the same request.
C. Call begin_analyze(), and then call poller.result() to retrieve the results.
D. Submit the PDF to an analyzer and read the results from the request headers.

Answer: C

Explanation:
To build an application that extracts fields from PDFs using Azure Content Understanding in Foundry Tools, you need to initialize the client library, use begin_analyze_binary to submit the file stream, and poll the long-running operation for the result.
Detail from implemenation:
Wait for the operation to complete and poll the results
result = poller.result()
Reference:
https://lobehub.com/pt-BR/skills/frank-luongt-faos-skills-marketplace-azure-ai-contentunderstanding-py

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
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:
Box: API endpoint
An API endpoint URL is what applications call to send requests to a deployed generative AI model.
Key Components of Deployed Model Requests
API Endpoint: The specific web address hosted by a cloud provider or server.
HTTP Method: Typically a POST request used to send data to the model.
Authentication: A secure API key passed in the request header to verify identity.
Payload: A JSON body containing the prompt, token limits, and temperature settings.
Reference:
https://help.sap.com/docs/sap-ai-core/generative-ai/consume-models

NEW QUESTION # 44
In which two scenarios can you use speech recognition? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. an in-car system that reads text messages aloud
B. creating a transcript of a telephone call or meeting
C. creating an automated public address system for a train station
D. providing closed captions for recorded or live videos

Answer: B,D

Explanation:
[A] Closed Captions
Goal: Show text on a screen for videos.
How it works:
Speech recognition matches spoken words with time codes.
This makes text appear on the screen as the audio plays.
[D] Transcript Creation
Goal: Write down everything said in a phone call or a meeting.
How it works:
An audio file is processed by a speech recognition tool.
The tool outputs a text document of the conversation.

NEW QUESTION # 45
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