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Microsoft AI-901 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 2	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.

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Microsoft Azure AI Fundamentals Sample Questions (Q25-Q30):

NEW QUESTION # 25
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 26
Your company wants to build a recycling machine for bottles. The recycling machine must use cameras to automatically identify bottles of the correct shape and reject all other items.
Which type of Al workload should the company use?

A. computer vision
B. natural language processing
C. knowledge mining
D. generative Al

Answer: A

Explanation:
A recycling machine that uses cameras to identify bottles of the correct shape and reject other items requires analysis of visual input. This is a computer vision workload.
Computer vision is used for image and video analysis tasks such as object detection, classification, shape recognition, and visual inspection.
The other options are incorrect:
A). knowledge mining extracts insights from large collections of documents or data.
B). natural language processing analyzes or generates language.
C). generative AI creates new content, but the requirement is to inspect camera images and identify objects.

NEW QUESTION # 27
You are deploying a generative Al model to a Microsoft Foundry project. You assign a higher tokens per minute (TPM) allocation to the model. What is the result of this change?

A. The speed and scale at which the model deployment can process inputs changes
B. The Azure region availability of the model changes.
C. The model generates longer responses.
D. The model generates shorter responses and additional source citations.

Answer: A

Explanation:
Tokens per minute, or TPM , is a throughput allocation for a model deployment. Assigning a higher TPM allocation increases the amount of token processing capacity available to the deployment, which affects the speed and scale at which the deployment can process requests.
It does not directly make responses longer, change region availability, or automatically add citations.

NEW QUESTION # 28
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 29
You are reviewing best practices for using AI at your company.
Which Microsoft responsible AI principle is each task an example of? To answer, drag the appropriate principles to the correct tasks. Each task 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 match is worth one point.

Answer:

Explanation:

NEW QUESTION # 30
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