Prepare with Microsoft AI-900 Korean exam practice material, pass for sure

Updated: Aug 06, 2026

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Introducing Updated Microsoft Certified: Azure AI Fundamentals Designation

This certificate is an opportunity for candidates to showcase their mastery of the Machine Learning (ML) and Artificial Intelligence (AI) workloads and their implementation of Azure services. For that reason, AI-900 exam can be taken by all candidates from technical and non-technical fields. While software engineering and data science skills may not be required for such an evaluation, it is important to have general programming knowledge to stand a chance of cracking this test right away. By and large, the updated Microsoft Certified: Azure AI Fundamentals designation can help you advance your career growth by preparing you for advanced Azure role-based certifications including the Microsoft Certified: Azure AI Engineer Associate and the Microsoft Certified: Azure Data Scientist Associate certificates.

The Microsoft AI-900 exam, usually known as the Microsoft Azure AI Fundamentals, is well suited to baseline-level IT specialists with knowledge of artificial intelligence (AI) & Machine Learning (ML), and the relevant Microsoft Azure concepts. This is the only test that you should pass to qualify for the Microsoft Certified: Azure AI Fundamentals certification.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

Skills measured

  • Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
  • Describe fundamental principles of machine learning on Azure (30-35%)
  • Describe AI workloads and considerations (15-20%)
  • Describe features of conversational AI workloads on Azure (15-20%)
  • Describe features of computer vision workloads on Azure (15-20%)

Schedule exam

Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian

Retirement date: none

Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.

Microsoft AI-900 Korean Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-900
Exam Format:Multiple choice, Multiple response, Drag and drop, Case studies
Available Languages:English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil)
Certificate Validity Period:Does not expire (Fundamentals certification)
Real Exam Qty:40-60
Exam Duration:85 minutes
Related Certifications:Microsoft Azure Data Fundamentals
Microsoft Azure Fundamentals
Microsoft Azure AI Engineer Associate
Passing Score:700/1000
Exam Price:USD 99 (varies by region)
Recommended Training:Microsoft Learn AI-900 Learning Path
Azure AI Fundamentals Practice Modules
Exam Registration:Pearson VUE Exam Registration
Official Microsoft Certification Page
Sample Questions:Microsoft AI-900 Korean 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/

Microsoft AI-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Features of computer vision workloads on Azure15-20%- Computer vision solutions
  • 1. Object detection
    • 2. Image classification
      • 3. OCR and image analysis
        Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
        • 1. Responsible AI principles
          • 2. Common AI workloads
            Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
            • 1. Sentiment analysis
              • 2. Key phrase extraction
                • 3. Language modeling and translation
                  Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
                  • 1. Training and validation concepts
                    • 2. Supervised vs unsupervised learning

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