Pass the actual test with the help of AI-900 中文 study guide
Updated: Oct 17, 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
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Related Certifications: | Microsoft Azure AI Engineer Associate Microsoft Azure Fundamentals Microsoft Azure Data Fundamentals |
| Exam Price: | USD 99 (varies by region) |
| Exam Format: | Case studies, Multiple response, Multiple choice, Drag and drop |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700/1000 |
| Exam Duration: | 85 minutes |
| Available Languages: | English, German, Japanese, French, Portuguese (Brazil), Korean, Chinese (Simplified), Spanish |
| Recommended Training: | Microsoft Learn AI-900 Learning Path Azure AI Fundamentals Practice Modules |
| Exam Registration: | Official Microsoft Certification Page Pearson VUE Exam Registration |
| Sample Questions: | Microsoft AI-900 中文 Sample Questions |
| 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/ |
The individuals who passed the Microsoft AI-900 exam possess the foundational knowledge of artificial intelligence (AI) and machine learning (ML). The test is designed to evaluate the candidates’ understanding of basic AI and ML workloads as well as how to execute them on Microsoft Azure. The students can earn the Microsoft Certified: Azure AI Fundamentals certification at the end of their journey with this path.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Topic 2: Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Topic 3: Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Topic 4: Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
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