Microsoft AI-900 Questions & Answers - in .pdf
- Total Q&A: 336
- Update: Aug 14, 2026
- Price: $59.99
- Vendor: Microsoft
- Exam Code: AI-900
- Exam Name: Microsoft Azure AI Fundamentals
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- Complete Microsoft Recommended Syllabus.
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- Exact Microsoft AI-900 Exam Questions with Correct Answers, verified by Experts with years of Experience in IT Field.
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Microsoft AI-900 Q&A - Testing Engine
- Total Q&A: 336
- Update: Aug 14, 2026
- Price: $59.99
- Vendor: Microsoft
- Exam Code: AI-900
- Exam Name: Microsoft Azure AI Fundamentals
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Describing AI-900 Exam Facts and Topics
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:
- Designing features of NLP (Natural Language Processing) workloads on Azure (15-20%);
- Defining features of conversational AI workloads on Azure (15-20%).
- Describing fundamental principles of machine learning on Azure (30-35%);
- Detailing Artificial Intelligence considerations and workloads (15-20%);
- Explaining features of computer vision workloads on Azure (15-20%);
Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI
- Identify features of common AI workloads
|
| Topic 2: Describe features of computer vision workloads on Azure | 15-20% | - Identify common computer vision tasks
- Identify Azure AI services for computer vision
- Describe Azure capabilities for computer vision
|
| Topic 3: 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
|
| Topic 4: 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
|
| Topic 5: Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify Azure AI services for NLP
- Identify common NLP tasks
- Describe Azure capabilities for NLP
|
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