Exam Name: Microsoft Azure AI Fundamentals
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Azure AI Fundamentals
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Updated: Oct 13, 2026
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- Total Questions: 336
- Updated on: Oct 13, 2026
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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: | 700/1000 |
| Exam Price: | USD 99 (varies by region) |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Real Exam Qty: | 40-60 |
| Related Certifications: | Microsoft Azure Data Fundamentals Microsoft Azure AI Engineer Associate Microsoft Azure Fundamentals |
| Available Languages: | Portuguese (Brazil), Japanese, German, French, Korean, English, Spanish, Chinese (Simplified) |
| Exam Duration: | 85 minutes |
| Exam Format: | Case studies, Drag and drop, Multiple choice, Multiple response |
| Recommended Training: | Azure AI Fundamentals Practice Modules Microsoft Learn AI-900 Learning Path |
| Exam Registration: | Pearson VUE Exam Registration Official Microsoft Certification Page |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam or in-person test center |
| Pre Condition: | No formal prerequisites required; basic understanding of cloud and AI concepts recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
AI-900 Exam FAQ: Hard Exam, Honest Help
Microsoft recommends these training resources for the Microsoft Azure AI Fundamentals exam:
Follow the training with steady self-testing — the 336 practice questions from ITCertMagic help you apply theory and fill any gaps the training leaves.
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 Azure Data Fundamentals, Microsoft Azure Fundamentals, Microsoft Azure AI Engineer Associate. Candidates in 2026 start with ITCertMagic'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.
ITCertMagic 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.
The official Microsoft Azure AI Fundamentals outline defines 4 domains. The leading three are Describe AI workloads and considerations (20-25%), Fundamentals of machine learning on Azure (25-30%), and Features of natural language processing (NLP) workloads on Azure (30-35%). The full list is in the topics section above, and ITCertMagic's 336 practice questions cover each one.
The Microsoft Azure AI Fundamentals exam contains 40-60 to complete within 85 minutes. Timed simulation in the ITCertMagic Desktop Test Engine teaches that rhythm before exam day does.
No formal prerequisites required; basic understanding of cloud and AI concepts recommended 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 Microsoft Azure AI Fundamentals exam requires 700/1000 to pass, and registration costs USD 99 (varies by region). A failed attempt means paying the same fee again — a readiness check with the ITCertMagic engines before booking is the cheaper option.
Online proctored exam or in-person test center Register for the Microsoft Azure AI Fundamentals exam through these official channels:
After booking, ITCertMagic delivers your practice questions within 1 minute — preparation starts the same day.
Microsoft Azure AI Fundamentals Sample Questions:
Match the Azure OpenAI large language model (LLM) process to the appropriate task.
To answer, drag the appropriate process from the column on the left to its task on the right. Each process may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) study material and Azure OpenAI Service documentation, large language models (LLMs) such as GPT are capable of performing multiple natural language processing (NLP) tasks depending on the intent of the prompt. These tasks generally fall into categories like classification, generation, summarization, and translation, each with a distinct purpose and output type.
* Classifying - This process involves analyzing text and assigning it to a predefined category or label based on its content. The scenario "Detect the genre of a work of fiction" clearly fits this category. The model must evaluate the text and determine whether it belongs to genres like mystery, romance, or science fiction. This is a classic text classification problem, as the output is a discrete category derived from textual features.
* Summarizing - This process means condensing lengthy text into a shorter version that preserves the key information. In the scenario "Create a list of bullet points based on text input," the model extracts essential information and reformats it as concise bullet points, which is an abstraction form of summarization. Summarization models help users quickly understand the main ideas from long documents, meeting efficiency and readability goals.
* Generating - This refers to the LLM's ability to produce new, creative content based on input instructions. The task "Create advertising slogans from a product description" represents generation because it requires the model to construct original text that didn't previously exist. Generation tasks showcase the creativity and contextual fluency of models like GPT in marketing and content creation.
Thus, these mappings align directly with the Azure OpenAI LLM capabilities taught in AI-900, linking each NLP process with its most suitable real-world task.
You need to provide customers with the ability to query the status of orders by using phones, social media, or digital assistants.
What should you use?
- A. the Azure Al Translator service
- B. an Azure Al Document Intelligence model
- C. Azure Al Bot Service
- D. an Azure Machine Learning model
Correct Answer: C 🗳️
Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).
You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.
This is an example of which type of natural language processing workload?
- A. sentiment analysis
- B. entity recognition
- C. language detection
- D. key phrase extraction
Correct Answer: A 🗳️
Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).
What ate two common use cases for generative Al solutions? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. creating original artwork from textual descriptions
- B. classifying email messages as spam or non-spam
- C. generating draft responses for customer service agents
- D. predicting sales revenue based on historical data
Correct Answer: A,C 🗳️
Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).
You need to determine the location of cars in an image so that you can estimate the distance between the cars.
Which type of computer vision should you use?
- A. image classification
- B. object detection
- C. face detection
- D. optical character recognition (OCR)
Correct Answer: B 🗳️
Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).
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