Exam Name: Microsoft Azure AI Fundamentals
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Azure AI Fundamentals
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Instant Download Microsoft : AI-900 Exam Dumps
Updated: Oct 26, 2026
No. of Questions: 336 Questions & Answers
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- Total Questions: 336
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- Total Questions: 336
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Microsoft AI-900 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Passing Score: | 700 (on a scale of 1–1000) |
| Exam Duration: | 45 minutes |
| Exam Format: | Multiple select, Scenario-based questions, Multiple choice |
| Available Languages: | Arabic (Saudi Arabia), Italian, Portuguese (Brazil), Korean, Indonesian (Indonesia), Russian, English, French, Chinese (Traditional), Japanese, Chinese (Simplified), German, Spanish |
| Certificate Validity Period: | Valid indefinitely |
| Exam Price: | $99 USD |
| Real Exam Qty: | 40–60 |
| Related Certifications: | Microsoft Certified: Azure Data Fundamentals Microsoft Certified: Azure Fundamentals |
| Recommended Training: | Instructor-led Training: AI-900 Course Microsoft Learn: Azure AI Fundamentals Learning Path |
| Exam Registration: | Microsoft Certification Registration Pearson VUE Registration |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or onsite testing at Pearson VUE test centers |
| Pre Condition: | No required prerequisites; basic familiarity with cloud computing or AI concepts is recommended but not mandatory |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900/ |
Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe capabilities of Azure Machine Learning - Describe machine learning pipelines - Describe core concepts of machine learning |
| Features of generative AI workloads on Azure | 20–25% | - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts - Describe responsible AI practices for generative AI - Describe use cases for generative AI |
| Features of computer vision workloads on Azure | 15–20% | - Identify types of computer vision solutions - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Face - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Custom Vision |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Translator - Identify types of NLP solutions - Describe capabilities of Azure Language - Describe capabilities of Azure Speech |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe responsible AI principles - Identify types of AI workloads - Describe considerations for developing AI solutions |
AI-900 Exam FAQ: Practical, Current, Expert-Built
No required prerequisites; basic familiarity with cloud computing or AI concepts is recommended but not mandatory Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.
Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 336 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
The AI-900 exam is a Microsoft certification exam validating the Microsoft Azure AI Fundamentals syllabus shown above. It belongs to these credential paths: Microsoft Certified: Azure Data Fundamentals, Microsoft Certified: Azure Fundamentals. Candidates in 2026 start with ActualTestsIT's 336 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
Microsoft recommends these training resources for the Microsoft Azure AI Fundamentals exam:
Follow the training with steady self-testing — the 336 practice questions from ActualTestsIT help you apply theory and fill any gaps the training leaves.
The official Microsoft Azure AI Fundamentals outline defines 5 domains. The leading three are Features of computer vision workloads on Azure (15–20%), Fundamental principles of machine learning on Azure (15–20%), and Features of generative AI workloads on Azure (20–25%). The full list is in the topics section above, and ActualTestsIT's 336 practice questions cover each one.
The Microsoft Azure AI Fundamentals exam contains 40–60 to complete within 45 minutes. Timed simulation in the ActualTestsIT Desktop Test Engine teaches that rhythm before exam day does.
The Microsoft Azure AI Fundamentals exam requires 700 (on a scale of 1–1000) to pass, and registration costs $99 USD. A failed attempt means paying the same fee again — a readiness check with the ActualTestsIT engines before booking is the cheaper option.
ActualTestsIT issues a full refund if you take the Microsoft Azure AI Fundamentals exam within 60 days of purchase and do not pass. The policy does not apply if the exam is taken within 3 days of purchase, if the exam was never actually taken, or to free materials or expired orders, and the candidate name must match the payer name. Submit a scan of your enrollment slip and the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Alternatively, exchange for two free exam products of equal value and keep your original update service. Orders arrive by email within 1 minute — contact support if nothing arrives within 2 hours.
Online proctored or onsite testing at Pearson VUE test centers Register for the Microsoft Azure AI Fundamentals exam through these official channels:
After booking, ActualTestsIT delivers your practice questions within 1 minute — preparation starts the same day.
Microsoft Azure AI Fundamentals Sample Questions:
What is an example of unsupervised machine learning?
- A. classification
- B. clustering
- C. regression
Correct Answer: B 🗳️
Explanation: Only visible for ActualTestsIT members. You can sign-up / login (it's free).
Select the answer that correctly completes the sentence.
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Identify features of common machine learning types", a regression model is a type of supervised machine learning model that is used to predict continuous numeric values based on one or more input variables (features).
In supervised learning, models are trained using labeled data, where each input record has a known target value (label). For regression specifically, the label represents a numeric quantity - such as price, age, temperature, or sales figures. The model learns to approximate a function that maps input variables to numeric outputs.
For example:
* Predicting house prices based on size, location, and number of rooms.
* Predicting monthly sales revenue from marketing spend and seasonality.
* Forecasting temperature based on historical weather data.
In Azure Machine Learning Designer and AutoML, when building a regression model, the label column must therefore be of numeric data type (integer or float). If the label were categorical (for example, "yes/no" or
"approved/denied"), the appropriate model type would be classification, not regression.
To contrast with other options:
* Boolean - used in binary classification problems (true/false outcomes).
* Datetime - used for time series forecasting, not standard regression labels.
* Text - used as input features for NLP models, not as regression targets.
Hence, when configuring a regression task in Azure, ensuring the target variable (label) is numeric is a fundamental requirement. The model's performance metrics-such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R²-also rely on numeric computations.
You need to track multiple versions of a model that was trained by using Azure Machine Learning. What should you do?
- A. Register the training data.
- B. Explain the model.
- C. Register the model.
- D. Provision an inference duster.
Correct Answer: C 🗳️
Explanation: Only visible for ActualTestsIT members. You can sign-up / login (it's free).
What is an advantage of using a custom model in Form Recognizer?
- A. A custom model is less expensive than a prebuilt model.
- B. A custom model always provides higher accuracy.
- C. A custom model can be trained to recognize a variety of form types.
- D. Only a custom model can be deployed on-premises.
Correct Answer: C 🗳️
Explanation: Only visible for ActualTestsIT members. You can sign-up / login (it's free).
You need to predict the animal population of an area.
Which Azure Machine Learning type should you use?
- A. classification
- B. clustering
- C. regression
Correct Answer: C 🗳️
Explanation: Only visible for ActualTestsIT members. You can sign-up / login (it's free).
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