Microsoft Azure AI Fundamentals Cheat Sheet 2026

The 30 highest-yield Microsoft Azure AI Fundamentals facts, distilled from real exam questions. Print it, save it as a PDF, or study it here — free, no sign-up.

1. In Azure ML, what is the role of an 'experiment'? → A logical container that groups and tracks related training runs
2. Which approach does Azure Responsible AI use to detect and mitigate bias in ML models? → Using the Fairness dashboard and Responsible AI tools to assess and mitigate bias
3. A hospital wants to predict which patients are at high risk of readmission within 30 days of discharge. Which type of ML task is this? → Binary classification
4. Find the Azure cloud service that includes serverless features. → All of the above
5. Which statement best describes the difference between AI and machine learning? → Machine learning is a subset of AI focused on learning from data
6. Which kind of machine learning should you employ to forecast the quantity of gift cards that will be sold over the course of the upcoming month? → regression
7. Which responsible AI principle ensures that AI systems do not disadvantage particular groups of people unfairly? → Fairness
8. You are developing an app with AI. Make sure the app adheres to the responsible AI guidelines. Which two guidelines ought to you abide by? → Implement a process of AI model validation as part of the software review process
9. A hospital uses AI to flag unusual patterns in patient vitals that may indicate a medical emergency. Which AI capability is being applied? → Anomaly detection
10. Choose every model that makes up Supervised ML. → Both a and b
11. In natural language processing, what does 'tokenization' refer to? → Splitting text into individual units such as words or subwords for processing
12. What are Azure Cognitive Services (now Azure AI Services)? → Pre-built AI APIs and models accessible via REST endpoints without requiring ML expertise
13. What is the purpose of the 'Content Moderator' service in Azure Cognitive Services? → To detect potentially offensive, risky, or unwanted content in text and images
14. Which Azure Machine Learning capability automates the process of selecting algorithms and tuning hyperparameters? → Automated ML (AutoML)
15. What is the primary purpose of Azure Bot Service? → To build, connect, and manage intelligent chatbots
16. Which Azure AI Vision feature can generate a dense description of all regions within an image? → Dense captioning
17. What platform offers a Conversation AI agent user interface? → Azure Bot Service
18. Which Azure AI capability is used to detect, identify, and verify human faces in images? → Azure Face API
19. What is the role of features in a machine learning model? → They are the input variables used to make predictions
20. What Azure service would you use to build a conversational bot that understands natural language queries? → Azure Bot Service with Azure AI Language (CLU)
21. Which concept describes the process of using a model trained on one task as the starting point for a different but related task? → Transfer learning
22. What does 'grounding' mean in the context of generative AI applications built with Azure AI? → Connecting model responses to your own specific, authoritative data sources
23. A company wants to detect whether a customer review is positive, negative, or neutral. Which AI technique is most appropriate? → Sentiment analysis
24. What is transfer learning in the context of AI model development? → Reusing a pre-trained model as a starting point and fine-tuning it for a new related task
25. In Azure Custom Vision, what does the 'Precision' metric indicate? → The percentage of predictions the model made that were actually correct
26. In conversational AI, what is an 'utterance'? → An example phrase or sentence that a user might say to the bot
27. Which Microsoft tool provides a dashboard for assessing error analysis, fairness, and model interpretability in Azure Machine Learning? → Responsible AI Dashboard in Azure Machine Learning
28. A retailer wants to automatically tag product images with descriptive labels. Which Azure Cognitive Services feature is most appropriate? → Image Analysis (Computer Vision)
29. What does 'precision' measure in a classification model evaluation? → The percentage of predicted positives that are truly positive
30. What does 'hyperparameter tuning' mean in Azure Machine Learning? → Searching for the optimal configuration settings that control the training process