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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 (Q26-Q31):

NEW QUESTION # 26
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:

Explanation:

A system prompt, also called a system message, is used to guide how a generative AI model behaves, including its tone, role, response style, and output format. Microsoft states that system messages help steer an Azure OpenAI chat model toward the desired behavior, tone, and output format.
Statement 1: System prompts can be used to authorize users. = No
Authorization is handled by application identity, access control, authentication, and security configuration. A system prompt can guide model behavior, but it is not an authorization mechanism.
Statement 2: A system prompt is used to reduce tokens per minute (TPM). = No TPM is a quota or throughput setting for model deployments. A system prompt does not reduce or configure TPM.
Statement 3: A system prompt guides the behavior of a generative AI model. = Yes This is correct. Microsoft documentation says system messages help steer the model's behavior, tone, and output format.


NEW QUESTION # 27
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 28
You have an AI-based loan approval system.
During testing, you discover that the system has a gender bias.
Which responsible AI principle does this violate?

Answer: C

Explanation:
Fairness is the responsible AI principle that addresses gender bias. It ensures that artificial intelligence systems treat all people fairly and do not create or spread unfair differences between groups based on gender, race, or other traits.
Stops Bias: It keeps systems from treating one group worse than another.
Checks Data: It looks at training data to remove unfair patterns.
Protects Users: It ensures equal outcomes for everyone.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai


NEW QUESTION # 29
What is an example of the Microsoft responsible Al principle of transparency?

Answer: C

Explanation:
The Microsoft responsible AI principle of transparency means AI systems should be understandable. Users should know when they are interacting with AI and should be able to understand the system's purpose, capabilities, limitations, and the basis for its decisions.
Therefore, helping users understand the decisions made by an AI system is an example of transparency .


NEW QUESTION # 30
Stating the source of the data used to train a model is an example of which responsible AI principle?

Answer: D

Explanation:
Transparency in AI refers to openly sharing information about how an AI system is designed, trained, and operates. Stating the source of the data used to train a model is an example of transparency, as it provides clarity about the origins of the data and helps stakeholders understand the model's development process.


NEW QUESTION # 31
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