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: Jun 01, 2026
  • Q & A: 328 Questions and Answers

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About Microsoft AI-900 Korean Exam Questions

Describe the Basic Principles of ML on Microsoft Azure (30-35%)

As for this area, it includes the following:

  • Explain the abilities of the No-code ML with Azure ML Learning Studio – This domain equips the individuals with the knowledge of the Azure ML designer and automated ML UI.
  • Describe the ML core concepts – You should be able to identify the labels and features within a dataset for ML and describe the usage of validation datasets and training in ML. The applicants also need the ability to explain the usage of ML algorithms in model training, as well as interpret and choose the model evaluation yardsticks for regression and classification.
  • Identify the basic ML types – This section equips the learners with the ability to identify various concepts, such as regression, clustering, and classification ML scenarios.
  • Identify the major tasks in crafting an ML solution – This subject area measures the students’ competence in explaining some concepts, such as basic features of data preparation and ingestion, model management and deployment, model training & evaluation, and feature selection and engineering.

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Microsoft AI-900 Korean Exam Syllabus Topics:

TopicDetails
Topic 1
  • Describe features of computer vision workloads on Azure: This topic discusses identifying common types of computer vision solution, Azure tools and services for computer vision tasks.
Topic 2
  • Describe features of Natural Language Processing (NLP) workloads on Azure: In this topic, questions about common NLP Workload Scenarios features, Azure tools, and services for NLP workloads appear.
Topic 3
  • Describe features of generative AI workloads on Azure: Features of generative AI solutions and capabilities of Azure OpenAI Service are discussed in this topic.
Topic 4
  • Describe fundamental principles of machine learning on Azure: It describes core machine learning concepts and Azure Machine Learning capabilities. Moreover, the topic also delves into identifying common machine-learning techniques.
Topic 5
  • Describe Artificial Intelligence workloads and considerations: It identifies specifications of common AI workloads and guiding principles for responsible AI.

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

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