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

AI-900日本語 real exams

Exam Code: AI-900J

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

Updated: Aug 03, 2026

Q & A: 336 Questions and Answers

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How much AZ-900:Microsoft Azure AI Fundamentals Exam Cost

The exam cost of Microsoft Azure AI Fundamentals is 99 USD.

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

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What is Microsoft AI-900 Exam

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. Explore the objectives of the AI-900 exam. Protection of the Azure platform and its components. Reference architecture for Azure solutions. Implementation, configuration, and management of Azure services. Request, manage and monitor Azure services. Troubleshooting of Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam takers level of competence in the functions, features, and services of Azure. Depth and Breadth of Knowledge. Processes and practices for developing and deploying intelligent solutions. Hope you like this article. Associate in IT, Eugene is an expert in the fields of software applications and internet technologies. Paying attention to the latest technology is the reason Eugene uses his knowledge of high-end computer systems, application programming, and data entry.

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Microsoft AI-900日本語 Exam Syllabus Topics:

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

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