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Last Updated: Jul 21, 2026
No. of Questions: 336 Questions & Answers with Testing Engine
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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The Microsoft AI-900 exam is the only qualifying test that leads to the Microsoft Certified: Azure AI Fundamentals certification. It measures one’s knowledge of AI considerations & workloads, features of NLP workloads on Azure, and basic principles of ML on Azure. The candidates can choose to take this exam in English, French, Simplified Chinese, Japanese, German, Spanish, or Korean. It contains 40-60 questions covering different types, including case studies, drag and drop, active screen, build list, and multiple choice. You can schedule your test with Certiport or Pearson VUE. However, it is required to pay the fee of $99 before scheduling it.
In case you're eager to get to know more about artificial intelligence facets & machine learning functions that relate to Microsoft Azure, then you're recommended to opt for AI-900 test.
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| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer |
| 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 Speech - Describe capabilities of Azure Language |
| Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe responsible AI principles - Describe considerations for developing AI solutions |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe machine learning pipelines - Describe core concepts of machine learning - Describe automated machine learning - Describe capabilities of Azure Machine Learning |
| Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe responsible AI practices for generative AI - Describe generative AI concepts - Describe capabilities of Azure OpenAI Service |
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