Pass Guaranteed Quiz 2026 Microsoft AI-901: Microsoft Azure AI Fundamentals–Valid Valid Exam Bootcamp

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Microsoft AI-901 Exam Syllabus Topics:

Section	Weight	Objectives
Describe fundamental principles of machine learning on Azure	25-30%	- Azure Machine Learning basics 1. AutoML concepts 2. Azure ML workspace components - Machine learning concepts 1. Regression and classification 2. Training and evaluation concepts 3. Supervised vs unsupervised learning
Describe features of computer vision workloads on Azure	15-20%	- Image analysis 1. Optical character recognition (OCR) 2. Image classification 3. Object detection - Azure AI Vision services 1. Azure AI Vision 2. Face detection and analysis (limited use cases)
Describe features of generative AI workloads on Azure	10-15%	- Azure OpenAI and generative services 1. Use cases: chatbots, content generation, summarization 2. Azure OpenAI Service capabilities - Generative AI concepts 1. Responsible use of generative AI 2. Large language models (LLMs) 3. Prompt engineering basics
Describe features of natural language processing (NLP) workloads on Azure	15-20%	- Text analysis 1. Key phrase extraction 2. Language detection 3. Sentiment analysis - Azure NLP services 1. Speech services (speech-to-text, text-to-speech) 2. Azure AI Language
Describe Artificial Intelligence workloads and considerations	20-25%	- Responsible AI principles 1. Privacy and security 2. Reliability and safety 3. Inclusiveness 4. Fairness 5. Transparency and accountability - Identify features of common AI workloads 1. Conversational AI and chatbots 2. Natural language processing use cases 3. Document processing and extraction 4. Computer vision use cases

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Microsoft Azure AI Fundamentals Sample Questions (Q38-Q43):

NEW QUESTION # 38
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

The completed sentence is:
When developing an AI system for self-driving cars, the Microsoft reliability and safety principle for responsible AI should be applied to ensure consistent operation of the system during use.
Self-driving cars are safety-critical AI systems. The key requirement in the question is consistent operation of the system during use , which maps directly to the Microsoft responsible AI principle of reliability and safety .
The other options are incorrect:
Fairness focuses on reducing bias and treating people equitably.
Accountability focuses on ensuring people remain responsible for AI systems and their outcomes.
Inclusiveness focuses on designing AI systems that work for and empower diverse users, including people with different needs or abilities.
Therefore, the correct answer is reliability and safety .

NEW QUESTION # 39
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:
Box: transcription
Azure Content Understanding in Foundry Tools uses transcription preprocessing to convert spoken words from audio and video files into text-based transcripts.
Optimized Preprocessing: Transcription runs as an initial extraction step to provide rich textual context before passing data to generative AI models.
Transcript Formatting: Conversational audio is turned into searchable WebVTT transcripts containing word-level or sentence-level timestamp.
Speaker Separation: Features like diarization identify and distinguish different speakers, while speaker role detection can pinpoint specific roles (such as agent and customer).
Multilingual Handling: It supports automatic language identification and multi-language phrase transcription.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/overview

NEW QUESTION # 40
You are developing an application that analyze invoices by using Azure Content Understanding in Foundry Tools.
You need to ensure that the application retrieves the analysis results after processing completes.
How should you complete the Python code? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 41
Your company provides users with clear information about an Al system ' s purpose, functionality, and limitations. Which Microsoft responsible Al principle is this an example of?

A. fairness
B. transparency
C. reliability and safety
D. accountability

Answer: B

Explanation:
Providing users with clear information about an AI system's purpose, functionality, and limitations is an example of the Microsoft responsible AI principle of transparency . Transparency means users should be able to understand when and how AI is being used, what the system can do, and what its limitations are.

NEW QUESTION # 42
For each of the following statement1, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Statement 1: Voice Live returns only transcribed text. = No
Voice Live is not limited to returning transcribed text. It is designed for real-time spoken conversational experiences and can include speech input, model reasoning, and spoken output.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services.
= No
Voice Live combines the conversational voice pipeline, so you do not need to separately build independent speech-to-text and text-to-speech services for the same real-time voice experience.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This statement is correct. Voice Live is used for real-time conversational AI experiences where spoken input is processed, the model reasons over the request, and spoken output can be returned.

NEW QUESTION # 43
......

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