AI-900日本語 exam dumps

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  • Exam Code: AI-900日本語
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900日本語版)
  • No. of Questions: 336 Questions and Answers
  • Updated: Sep 07, 2026

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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 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 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 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 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.

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How to Prepare For AI-900: Microsoft Azure AI Fundamentals

Preparation Guide for AI-900: Microsoft Azure AI Fundamentals

Introduction

Microsoft AI-900 exam is designed for Microsoft partners who are certified by Microsoft to integrate Microsoft Azure Intelligent Solutions into their own products and solutions. The objective of the certification is to verify that approved partners have the knowledge and skills to deploy, configure, set up, activate, maintain, troubleshoot, and support all necessary Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam taker level of competence in the functions, features, and services of Azure. The Microsoft AI-900 Certification Exam is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017, and NET Framework. Courses are available online or in-person depending on individual needs.

This article will cover the areas of knowledge required for this exam, how many questions are covered in each area, and who is taking this certification exam.

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

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