practice · AI-901

AI-901 Practice Exam — 45 Azure AI Fundamentals Questions with Answers

A full-length AI-901 Microsoft Azure AI Fundamentals practice exam with 45 scenario questions, timed reveals, answer explanations, and source-backed review cues.

Video summary

AI-901 exam course video: 45-question AI-901 full-length practice exam. Learn Microsoft Azure AI Fundamentals concepts with WebLizard Cert Lab.

Study notes

  • Chapter coverage includes Cold open / title and Object detection in computer vision.
  • Later coverage includes Speech, synthesis, and text summarization and Thank You / next step.

Practice exam summary

This full-length AI-901 practice exam includes 45 original, exam-style scenarios based on the public AI-901 objectives and Microsoft Learn documentation. Each question includes time to answer before the reveal, a clear explanation of the correct choice, and the related objective area.

What this helps you practice

  • Recognizing Azure AI Foundry, Azure AI services, and generative AI application patterns
  • Separating responsible AI, safety, evaluation, and human-review requirements
  • Reading scenario wording before jumping to a familiar product name
  • Using missed questions as a study map for weak AI-901 domains

How to use it

  1. Pause or answer before the reveal.
  2. Say why the other options are wrong.
  3. Listen for the exam clue and write down weak topics.
  4. Re-run missed questions after reviewing the study hub or Microsoft Learn.

Source-backed positioning

Use this source-backed practice exam to review AI-901 concepts and strengthen your reasoning. Exam objectives and product behavior can change. Check the current Microsoft Learn study guide first, then use these questions to test whether the concepts stick.

Chapters

  1. Cold open / title
  2. Audience / readiness
  3. How to use this exam
  4. Question type primer
  5. Start exam transition
  6. Q1: Responsible AI fairness
  7. Q2: Reliability and safety
  8. Q3: Privacy, security, and accountability
  9. Q4: Responsible AI in high-impact workflows
  10. Q5: Transparency and responsible AI
  11. Q6: Multimodal model selection
  12. Q7: Model deployment and SDK configuration
  13. Q8: Model configuration concepts
  14. Q9: System instructions and prompt roles
  15. Q10: Choosing models by modality
  16. Q11: Recognizing generative AI workloads
  17. Q12: Text analysis capabilities
  18. Q13: Speech recognition vs speech synthesis
  19. Q14: AI workload categories
  20. Q15: Object detection in computer vision
  21. Q16: Workload and model selection process
  22. Q17: Multi-workload AI solution decomposition
  23. Q18: Image generation workload recognition
  24. Q19: Agentic AI concepts
  25. Q20: Deploying and testing models in Foundry
  26. Q21: Foundry generative AI app workflow
  27. Q22: Prompt design for reliable support assistants
  28. Q23: Foundry agents vs simple generative AI interactions
  29. Midpoint checkpoint
  30. Q24: Foundry SDK and client app integration
  31. Q25: Foundry agents with tools and actions
  32. Q26: Foundry components and workflow roles
  33. Q27: Grounding with trusted context or retrieval
  34. Q28: Foundry playground prompt testing
  35. Q29: Sentiment analysis for customer comments
  36. Q30: Speech recognition and synthesis
  37. Q31: Speech, synthesis, and text summarization
  38. Q32: Text summarization for support notes
  39. Q33: Voice-enabled support app workflow
  40. Q34: Multimodal visual input
  41. Q35: Vision understanding and image generation
  42. Q36: Matching visual workload capabilities
  43. Q37: Image generation from text prompts
  44. Q38: Responsible image-generation workflow
  45. Q39: Structured document and form extraction
  46. Q40: Content Understanding input types
  47. Q41: Reliable extraction workflow setup
  48. Q42: Structured invoice field extraction
  49. Q43: Multimodal audio and video extraction
  50. Q44: Foundry Tools for repeatable structured extraction
  51. Q45: End-to-end extraction app with human review
  52. Confidence Builder
  53. Thank You / next step