Reliable AI-901 Exam Syllabus & AI-901 Exam Book

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Microsoft AI-901 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-900
Real Exam Qty:40-60
Passing Score:700 / 1000
Related Certifications:Microsoft Certified: Azure AI Fundamentals
Certificate Validity Period:1 year (renewable via free online assessment on Microsoft Learn)
Exam Price:USD 99
Exam Format:Match the service to use case, Drag and drop, Scenario-based, Multiple select, Multiple choice
Available Languages:English, French, Russian, Indonesian (Indonesia), Chinese (Traditional), Italian, German, Japanese, Arabic (Saudi Arabia), Portuguese (Brazil), Spanish, Korean, Chinese (Simplified)
Exam Duration:45-60
Sample Questions:Microsoft AI-901 Sample Questions
Exam Way:Online (remote proctored via Pearson VUE) or at a Pearson VUE test center
Pre Condition:No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900

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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.

Microsoft Azure AI Fundamentals Sample Questions (Q19-Q24):

NEW QUESTION # 19
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:

Explanation:
Fairness
Privacy and security
Transparency
Reliability and safety
Comprehensive and Detailed Explanation with all Azure AI documents: =
Evaluating model outputs to ensure that decisions are NOT biased against specific demographic groups:
Fairness
Microsoft's responsible AI principle of fairness means AI systems should treat people fairly and avoid unfair bias across demographic groups.
Encrypting sensitive customer data and restricting system access to authorized personnel: Privacy and security The privacy and security principle requires AI systems to protect personal and sensitive data and prevent unauthorized access.
Informing users when they are interacting with an AI system and explaining the system's capabilities and limitations: Transparency The transparency principle requires that people understand when they are interacting with AI and understand the system's purpose, capabilities, and limitations.
Testing AI systems under different conditions to reduce unexpected failures: Reliability and safety The reliability and safety principle means AI systems should operate reliably and safely, including through testing and validation under expected and unexpected conditions.


NEW QUESTION # 20
You need to build an AI solution that generates marketing email drafts based on a short description of a product and its target audience. Which AI workload should you use?

Answer: B

Explanation:
Generating marketing email drafts from a short product description and target audience is a content generation task. This is a generative AI workload because the system creates new text based on the user's prompt.


NEW QUESTION # 21
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each connect selection is worth one point.

Answer:

Explanation:

Explanation:

Statement 1: Using Azure Speech in Foundry Tools for batch transcription requires live audio input from a microphone. = No Batch transcription is used to process stored audio files, not live microphone input. Live microphone input is used for real-time speech recognition scenarios.
Statement 2: Azure Speech in Foundry Tools can analyze video frames to detect and label objects while transcribing audio. = No Azure Speech is for speech capabilities such as speech recognition, speech synthesis, and speech translation.
Detecting and labeling objects in video frames is a computer vision/video analysis capability, not an Azure Speech capability.
Statement 3: Speech translation in Azure Speech in Foundry Tools can translate spoken audio into text in another language. = Yes Speech translation converts spoken input in one language into translated text in another language.


NEW QUESTION # 22
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 23
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 # 24
......

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