Azure AI Fundamentals · 43% of the exam

Identify AI concepts and capabilities: free practice questions

5 sample questions from our 50-question bank for this domain — answers and explanations included. These are the same scenario-based style as the real Azure exam.

1. A voice assistant needs to convert a user's spoken words into text so it can process the request. Which Azure AI Speech capability is this?

  • A. Speech-to-text (speech recognition)✓ Correct
  • B. Text-to-speech (speech synthesis)
  • C. Sentiment analysis
  • D. Optical character recognition
Explanation

Transcribing spoken audio into text is speech-to-text (speech recognition). Text-to-speech (B) is the reverse — generating spoken audio from text. Sentiment analysis (C) works on text emotion, and OCR (D) reads text from images.

2. Which Azure AI service provides prebuilt text-analysis features such as sentiment analysis, key phrase extraction, language detection, and entity recognition?

  • A. Azure AI Language✓ Correct
  • B. Azure AI Vision
  • C. Azure AI Document Intelligence
  • D. Azure AI Face
Explanation

Azure AI Language bundles core text NLP features: sentiment, key phrases, language detection, and entity recognition. Azure AI Vision (B) analyzes images, Document Intelligence (C) extracts form fields, and Face (D) analyzes faces — none is the general text-analysis service.

3. In the context of large language models, what is a TOKEN?

  • A. A chunk of text (a word or part of a word) that the model processes as a unit✓ Correct
  • B. A security credential for signing in to Azure
  • C. A pixel in a generated image
  • D. A row in a relational table
Explanation

LLMs break text into tokens — words or sub-word pieces — which are the units they read and generate, and which usage/pricing are measured in. Option B confuses it with an authentication token. Option C (pixel) and option D (table row) are unrelated to how language models represent text.

4. A company builds an AI service and ensures it can be used by people with a wide range of abilities, including those who rely on assistive technologies. Which responsible AI principle is being applied?

  • A. Inclusiveness✓ Correct
  • B. Fairness
  • C. Accountability
  • D. Reliability and safety
Explanation

Designing AI to empower everyone and engage people across abilities and backgrounds is the inclusiveness principle. Fairness (B) is specifically about equitable treatment and avoiding bias in outcomes. Accountability (C) concerns human responsibility. Reliability and safety (D) concerns consistent, safe operation.

5. An organization publishes a document describing what its AI recommendation system does, what data it uses, and where it may be unreliable. Which principle is this practice MOST aligned with?

  • A. Transparency✓ Correct
  • B. Privacy and security
  • C. Reliability and safety
  • D. Inclusiveness
Explanation

Clearly communicating how the system works, what data it uses, and its limitations is the essence of transparency. Privacy and security (B) is about protecting data, reliability and safety (C) about consistent safe operation, and inclusiveness (D) about serving diverse users — the disclosure described maps most directly to transparency.

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