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

  • Exam Code: AI-900-KR
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900 Korean Version)
  • Updated: Sep 09, 2026
  • Q & A: 336 Questions and Answers

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About Microsoft AI-900 Korean Exam Questions

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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:

  • Defining features of conversational AI workloads on Azure (15-20%).
  • Describing fundamental principles of machine learning on Azure (30-35%);
  • Explaining features of computer vision workloads on Azure (15-20%);
  • Detailing Artificial Intelligence considerations and workloads (15-20%);
  • Designing features of NLP (Natural Language Processing) workloads on Azure (15-20%);

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

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In case you're eager to get to know more about artificial intelligence facets & machine learning functions that relate to Microsoft Azure, then you're recommended to opt for AI-900 test.

Exam Overview

This certification test is available in English, Spanish, Simplified Chinese, Japanese, French, Korean, and German. You will find different formats of questions while dealing with this Microsoft exam. These include multiple choice, drag and drop, build list, active screen, short answer, and best answer. The test costs $99 and the learners can register for it through Pearson VUE or Certiport.

Microsoft AI-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Fundamental principles of machine learning on Azure15–20%- Describe capabilities of Azure Machine Learning
- Describe core concepts of machine learning
- Describe machine learning pipelines
- Describe automated machine learning
Topic 2: Features of generative AI workloads on Azure20–25%- Describe capabilities of Azure OpenAI Service
- Describe use cases for generative AI
- Describe responsible AI practices for generative AI
- Describe generative AI concepts
Topic 3: Artificial Intelligence workloads and considerations15–20%- Identify types of AI workloads
- Describe considerations for developing AI solutions
- Describe responsible AI principles
Topic 4: Features of Natural Language Processing (NLP) workloads on Azure15–20%- Describe capabilities of Azure Language
- Describe capabilities of Azure Speech
- Describe capabilities of Azure Translator
- Identify types of NLP solutions
Topic 5: Features of computer vision workloads on Azure15–20%- Describe capabilities of Azure Face
- Identify types of computer vision solutions
- Describe capabilities of Azure Computer Vision
- Describe capabilities of Azure Custom Vision
- Describe capabilities of Azure Form Recognizer

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