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Microsoft Microsoft Certified: Azure AI Fundamentals AI-900-KR

AI-900 Korean

Exam Code: AI-900-KR

Exam Name: Microsoft Azure AI Fundamentals (AI-900 Korean Version)

Updated: Aug 14, 2026

Q & A: 336 Questions and Answers

AI-900-KR Free Demo download:

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AI-900 Korean PDF Price: $139.00  $69.99


About Microsoft AI-900-KR Exam

The Microsoft AI-900 exam will measure the candidates’ skills and competence in a range of topics. They are as follows:

  • Explain the Fundamental Principles of ML on Azure (30-35%): The potential candidates for the Microsoft AI-900 exam should be able to identify the common types of machine learning and explain its core concepts. They also need to know how to identify the core tasks that are involved in creating the ML solutions. Additionally, they need to have the knowledge of the capabilities of no-code ML with Azure ML studio.
  • Explain the Features of NLP (Natural Language Processing) Workloads Available on Azure (15-20%): This subject area will measure your ability to identify the features of basic Natural Language Processing Workload scenarios. It will also test your skills in identifying different Azure services and tools for NLP workloads. The topic will cover the understanding of the capabilities of Text Analytics service, Language Understanding service, Speech service, and Translator Text service.
  • Explain the Features of Computer Vision Workloads Available on Azure (15-20%): This domain requires that the test takers demonstrate competence in identifying the basic categories of computer vision solutions. It will also measure their skills in identifying different Azure services and tools for computer vision tasks. You will also need an understanding of the capabilities of Computer Vision service, Custom Vision service, Face service, and Form Recognizer service.
  • Explain AI Workloads & Considerations (15-20%): This section will measure the individuals’ ability to identify different features of common artificial intelligence workloads. It will also evaluate their competence in identifying the guiding principles that are responsible for AI.
  • Explain the Features of Conversational Artificial Intelligence Workloads Available on Azure (15-20%): The applicants must demonstrate the understanding of common use cases associated with conversational artificial intelligence. This area also measures one’s knowledge of Azure services associated with conversational artificial intelligence.

Skills measured

  • Describe fundamental principles of machine learning on Azure (30-35%)
  • Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
  • 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%)

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.

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

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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.

Microsoft AI-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Features of generative AI workloads on Azure20–25%- Describe generative AI concepts
- Describe capabilities of Azure OpenAI Service
- Describe use cases for generative AI
- Describe responsible AI practices for generative AI
Artificial Intelligence workloads and considerations15–20%- Describe responsible AI principles
- Identify types of AI workloads
- Describe considerations for developing AI solutions
Fundamental principles of machine learning on Azure15–20%- Describe automated machine learning
- Describe core concepts of machine learning
- Describe capabilities of Azure Machine Learning
- Describe machine learning pipelines
Features of computer vision workloads on Azure15–20%- Describe capabilities of Azure Custom Vision
- Describe capabilities of Azure Face
- Describe capabilities of Azure Form Recognizer
- Identify types of computer vision solutions
- Describe capabilities of Azure Computer Vision
Features of Natural Language Processing (NLP) workloads on Azure15–20%- Describe capabilities of Azure Language
- Identify types of NLP solutions
- Describe capabilities of Azure Translator
- Describe capabilities of Azure Speech

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