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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 Code: AI-900J
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900日本語版)
  • Updated: May 10, 2025
  • Q & A: 287 Questions and Answers
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About Microsoft AI-900日本語 Exam

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Certification Path of Microsoft AI-900 Exam

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

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Prerequisites

Microsoft AI-900 is a foundational-level certification exam. Therefore, the potential candidates are required to possess basic knowledge of the AI and ML concepts. They also need to have an understanding of the associated Microsoft Azure services. These individuals can have technical or non-technical backgrounds. They do not need to have software engineering or science experience before taking the test. However, some programming experience or knowledge would be an advantage for them.

The AI-900 exam is designed to validate the students’ knowledge of AI workloads & considerations, as well as attributes of computer vision workloads within Azure. It also certifies their understanding of the basic principles of ML on Azure and attributes of conversational Artificial Intelligence workloads on Azure. The applicants are also required to demonstrate their knowledge of the attributes of NLP (Natural Language Processing) workloads on Azure.

Microsoft AI-900 Exam Syllabus Topics:

TopicDetails

Describe Artificial Intelligence workloads and considerations (20-25%)

Identify features of common AI workloads- identify features of anomaly detection workloads
- identify computer vision workloads
- identify natural language processing workloads
- identify knowledge mining workloads
Identify guiding principles for responsible AI- describe considerations for fairness in an AI solution
- describe considerations for reliability and safety in an AI solution
- describe considerations for privacy and security in an AI solution
- describe considerations for inclusiveness in an AI solution
- describe considerations for transparency in an AI solution
- describe considerations for accountability in an AI solution

Describe fundamental principles of machine learning on Azure (25-30%)

Identify common machine learning types- identify regression machine learning scenarios
- identify classification machine learning scenarios
- identify clustering machine learning scenarios
Describe core machine learning concepts- identify features and labels in a dataset for machine learning
- describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning studio- automated machine learning
- azure Machine Learning designer

Describe features of computer vision workloads on Azure (15-20%)

Identify common types of computer vision solution- identify features of image classification solutions
- identify features of object detection solutions
- identify features of optical character recognition solutions
- identify features of facial detection, facial recognition, and facial analysis solutions
Identify Azure tools and services for computer vision tasks- identify capabilities of the Computer Vision service
- identify capabilities of the Custom Vision service
- identify capabilities of the Face service
- identify capabilities of the Form Recognizer service

Describe features of Natural Language Processing (NLP) workloads on Azure (25-30%)

Identify features of common NLP Workload Scenarios- identify features and uses for key phrase extraction
- identify features and uses for entity recognition
- identify features and uses for sentiment analysis
- identify features and uses for language modeling
- identify features and uses for speech recognition and synthesis
- identify features and uses for translation
Identify Azure tools and services for NLP workloads- identify capabilities of the Language service
- identify capabilities of the Speech service
- identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure- identify features and uses for bots
- identify capabilities of the Azure Bot service

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About Exam AI-900

The interested candidate for the Microsoft AI-900 test, which also goes under the name the Azure test for AI Fundamentals, should have at least some foundational understanding of the concept of AI features alongside ML ones. This exam will test the entrant's knowledge of different AI common workloads, principles of AI and ML, NLP workloads, and other related concepts. When it comes to the details for this exam, the Microsoft AI-900 is available in several languages, among which you'll find Spanish, English, Korean, German, Chinese (Simplified), and French. Such an exam comes with a registration fee of $99 and should be scheduled through Pearson VUE. Also, in the main exam, candidates will be exposed to around 40-60 tasks with 1 hour given to solve them.

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