Free PDF Quiz 2026 AI-901: Microsoft Azure AI Fundamentals–Valid Valid Mock Exam

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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
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 (Q60-Q65):

NEW QUESTION # 60
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:
Box 1: Named Entity Recognition (NER)
Named Entity Recognition (NER) is used to extract dates, quantities, and locations from text, along with other categories like names of people, organizations, and monetary values.
Reference:
https://www.iamdave.ai/blog/understanding-named-entity-recognition-ner-meaning-methods-and-use-cases/


NEW QUESTION # 61
What is an example of the Microsoft responsible AI principle of transparency?

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 # 62
You have a Microsoft Foundry project that has a generative AI model deployment.
You need to ensure that responses generated by the model minimize costs and remain within a defined length.
Which parameter should you configure?

Answer: D

Explanation:
The Max Completion Tokens (or max_tokens / max_output_tokens in the API) parameter is exactly the tool you use to enforce a fixed length on AI-generated responses and keep costs predictable.
How the Parameter Works
What it does: It sets a strict upper bound on the number of output tokens the model can generate for your completion. Once this number is reached, the model will stop generating (cut off) regardless of whether it finished its thought.
What it doesn't do: It does not set a minimum length or force the model to write exactly that amount. It only acts as a ceiling.
Reference:
https://learn.microsoft.com/en-us/answers/questions/5828812/reasoning-models-like-5-1-fails-with-500-error-cod


NEW QUESTION # 63
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 64
Hotspot Question
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 # 65
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