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Microsoft Azure AI Fundamentals (AI-900日本語版) : AI-900日本語

AI-900日本語 Exam Simulator
  • Exam Code: AI-900J
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900日本語版)
  • Updated: Aug 18, 2026
  • Q & A: 336 Questions and Answers
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Exam AI-900: Microsoft Azure AI Fundamentals

Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.

This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.

Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure AI Fundamentals

Download exam skills outline

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

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Microsoft AI-900日本語 Exam Syllabus Topics:

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

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