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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 (Q74-Q79):

NEW QUESTION # 74
You are authoring a Conversational Language Understanding application to support a music festival.
You want users to be able to ask questions about scheduled shows, such as: "Which act is playing on the main stage?" The question "Which act is playing on the main stage?" is an example of which type of element?

A. an intent
B. an entity
C. a domain
D. an utterance

Answer: D

NEW QUESTION # 75
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 76
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

When using the OpenAI Responses API and a vision-enabled model, you can include an image in a request by providing the image as a base64-encoded image data .
Azure OpenAI / Microsoft Foundry vision requests support image input as an input_image item. The image can be provided by URL or as base64-encoded image data in the request. Microsoft documentation for Azure OpenAI batch examples also lists Base64 encoded image and Image URL as supported input patterns for Responses API requests.
The other options are incorrect:
a CSV file attachment is not an image input format for vision analysis.
an MP4 video stream is video content, not an image format.
a shared access signature (SAS) token is only an access token for a protected resource; it is not the image data itself.

NEW QUESTION # 77
What is an example of the Microsoft responsible AI principle of transparency?

A. helping users understand the decisions made by an AI system
B. ensuring that the privileged data of users is stored in a secure manner
C. ensuring that developers are accountable for the solutions they create
D. ensuring that opportunities are allocated equally to all applicants

Answer: A

Explanation:
Transparency
Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Each predictive value should be broken down into individual features or vectors by importance or impact and deliver thorough prediction explanations that can be exported into a business report for audit and compliance reviews, customer transparency, and business readiness.
Transparency Notes provide our customers with information about the intended uses, capabilities, and limitations of our AI platform services.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://www.microsoft.com/en-us/ai/responsible-ai

NEW QUESTION # 78
You are explaining generative AI workflows to a colleague. What is the first step of a generative AI workflow?

A. Fine-tune a model by using feedback.
B. Train a generative AI model by using data.
C. Deploy a generative AI model.
D. Generate outputs based on user prompts.

Answer: B

NEW QUESTION # 79
......

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