Microsoft Azure AI Fundamentals : AI-901 Exam

  • Exam Code: AI-901
  • Exam Name: Microsoft Azure AI Fundamentals
  • Updated: Oct 17, 2026
  • Q & A: 132 Questions and Answers

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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.

Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-901

Microsoft Azure AI Fundamentals Sample Questions:

Question #1

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reveal Solution  Discussion  0

Correct Answer:


Question #2

You are using the Azure Speech SDK to develop a Python application that supports real-time spoken conversations.
Which Azure speech class should you use to configure the connection to the Azure Speech service?

  • A. AuditOutputConfig
  • B. AudioConfig
  • C. SpeechSynthesizer
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #3

Which natural language processing feature can be used to identify the main talking points in customer feedback surveys?

  • A. entity recognition
  • B. language detection
  • C. translation
  • D. key phrase extraction
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #4

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:

Statement 1: Voice Live returns only transcribed text. = No
Voice Live is not limited to transcription. Microsoft documentation states that the Voice Live API supports real-time bidirectional voice applications, including speech recognition, text-to-speech synthesis, avatar streaming, animation data, and audio processing.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services. = No Voice Live provides a single real-time voice API experience rather than requiring separate STT and TTS implementations for the conversational loop. Microsoft describes live AI voice conversations as combining speech capabilities for real-time interaction, and the Voice Live API includes speech recognition and text-to- speech synthesis features.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This is correct. Microsoft's guidance explains that Azure OpenAI audio/realtime capabilities are for scenarios that combine audio with language understanding, reasoning, or generation in a single model call, and Voice Live supports real-time voice-enabled applications over WebSocket connections.

Question #5

Select the answer that correctly completes the sentence.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:
Speech
The correct answer is speech . The scenario specifically describes converting spoken customer requests into written text , which is a speech-to-text , or speech recognition, capability. Microsoft classifies speech as one of the common AI workloads in the current Azure AI Fundamentals study guide. The guide explicitly requires candidates to identify scenarios involving speech and to understand the capabilities of speech recognition and speech synthesis .
Microsoft Azure Speech in Foundry Tools provides speech-to-text functionality that converts audio streams into textual transcriptions. It supports real-time transcription, fast transcription, and batch transcription depending on the workload.
Key phrase extraction analyzes existing text to identify important words or concepts; it does not perform audio transcription. Text analysis covers operations such as sentiment analysis, entity recognition, summarization, and key phrase extraction after text already exists. Natural Language Understanding (NLU) interprets the meaning or intent of language, but the conversion from audio into written words itself is specifically a speech recognition workload .
Study Guide Reference: Identify AI concepts and capabilities # Identify AI workloads # Identify features and capabilities of speech recognition and speech synthesis.

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