Updated: Aug 01, 2026
No. of Questions: 336 Questions & Answers with Testing Engine
Download Limit: Unlimited
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In general, AI-900 is a computer-based exam that’s available in English, Chinese, Japanese, Spanish, French, German, and Korean languages. It costs $99 for every attempt and can be scheduled with Certiport or Pearson VUE. Recently, the AI-900 exam curriculum has been updated to reflect the following skills as contained in the official study guide:
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
| Certification Vendor: | Microsoft |
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Exam Price: | USD 99.00 |
| Exam Format: | Single-choice, Multiple-choice, True/False, Drag and drop, Sequence ordering |
| Certificate Validity Period: | No expiration (certification does not expire) |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700/1000 |
| Available Languages: | English, Japanese, Chinese (Simplified), Korean, Spanish, French, German, Portuguese (Brazil), Indonesian |
| Exam Duration: | 45-60 |
| Sample Questions: | Microsoft AI-900 Sample Questions |
| Exam Way: | Online proctored exam or in-person testing center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required. Basic knowledge of cloud computing concepts is recommended but not mandatory. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/ai-900/ |
The Microsoft AI-900: Microsoft Azure AI Fundamentals exam is aimed at those professionals who want to demonstrate their knowledge of basic Machine Learning (ML) and Artificial Intelligence (AI) workloads. The test evaluates their understanding of how to implement both ML and AI on Azure. The candidates who pass this exam are eligible for the Microsoft Certified: Azure AI Fundamentals certification.
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Here, the following skills will be measured:
| Section | Weight | Objectives |
|---|---|---|
| Describe features of Generative AI workloads on Azure | 15-20% | - Describe generative AI concepts - Describe Azure OpenAI Service capabilities - Identify responsible AI considerations for generative AI |
| Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Describe features of computer vision workloads on Azure | 15-20% | - Describe Azure capabilities for computer vision - Identify common computer vision tasks - Identify Azure AI services for computer vision |
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Identify Azure AI services for NLP - Describe Azure capabilities for NLP |
| Describe fundamental principles of machine learning on Azure | 30-35% | - Describe features of no-code automated ML - Identify common machine learning tasks - Describe Azure Machine Learning capabilities - Describe core machine learning concepts |
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