Microsoft Azure AI Fundamentals (AI-900 Korean Version): AI-900 Exam
"Microsoft Azure AI Fundamentals (AI-900 Korean Version)", also known as AI-900 exam, is a Microsoft Certification. With the complete collection of questions and answers, PrepAwayPDF has assembled to take you through 336 Q&As to your AI-900 Exam preparation. In the AI-900 exam resources, you will cover every field and category in Microsoft Certified: Azure AI Fundamentals Certification helping to ready you for your successful Microsoft Certification.
- Exam Code: AI-900
- Exam Name: Microsoft Azure AI Fundamentals (AI-900 Korean Version)
- Certification Provider: Microsoft
- Corresponding Certification: Microsoft Certified: Azure AI Fundamentals
- Updated: Aug 09, 2026
- No. of Questions: 336 Questions & Answers with Testing Engine
- Download Limit: Unlimited
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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.
Exam Details
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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Topic 2: Describe features of computer vision workloads on Azure | 15-20% | - Identify common computer vision tasks - Describe Azure capabilities for computer vision - Identify Azure AI services for computer vision |
| Topic 3: Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe Azure OpenAI Service capabilities - Describe generative AI concepts |
| 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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