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The Microsoft AI-901 certification exam is an industrial-recognized Microsoft Azure AI Fundamentals (AI-901) certificate that is designed to validate candidates' skills, experience, and knowledge quickly. The Microsoft Azure AI Fundamentals (AI-901) certification exam has been inspiring Microsoft professionals since its beginning. Now this AI-901 certification exam has become solid proof of certain skills set and knowledge.

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.

>> Exam AI-901 Overviews <<

Real Microsoft AI-901 Torrent, AI-901 Latest Braindumps Sheet

The Microsoft AI-901 certification exam is an industrial-recognized Microsoft Azure AI Fundamentals (AI-901) certificate that is designed to validate candidates' skills, experience, and knowledge quickly. The Microsoft Azure AI Fundamentals (AI-901) certification exam has been inspiring Microsoft professionals since its beginning. Now this AI-901 certification exam has become solid proof of certain skills set and knowledge.

Microsoft Azure AI Fundamentals Sample Questions (Q75-Q80):

NEW QUESTION # 75
Verifying that machine learning models do NOT show racial or gender bias is an example of which Microsoft responsible AI principle?

Answer: C

Explanation:
Fairness and inclusiveness in Azure Machine Learning: The fairness assessment component of the Responsible AI dashboard enables data scientists and developers to assess model fairness across sensitive groups defined in terms of gender, ethnicity, age, and other characteristics.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai?view=azureml-api-2


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

Answer:

Explanation:


NEW QUESTION # 77
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 # 78
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

Evaluating model outcomes across demographic groups to reduce bias is an example of the Microsoft responsible AI principle of fairness.
The Microsoft responsible AI principle of fairness means AI systems should treat all people fairly and avoid unfair bias or discrimination across groups.
The other options are incorrect:
accountability means people and organizations remain responsible for AI systems and their effects.
privacy and security focuses on protecting data and controlling access.
transparency means users should understand when and how AI is being used, including system capabilities and limitations.


NEW QUESTION # 79
Verifying that machine learning models do NOT show racial or gender bias is an example of which Microsoft responsible AI principle?

Answer: C

Explanation:
Fairness and inclusiveness in Azure Machine Learning: The fairness assessment component of the Responsible AI dashboard enables data scientists and developers to assess model fairness across sensitive groups defined in terms of gender, ethnicity, age, and other characteristics.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai?view=azureml-api-2


NEW QUESTION # 80
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