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Microsoft Microsoft Certified: Azure AI Fundamentals AI-900-CN

AI-900-CN

Exam Code: AI-900-CN

Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)

Updated: Aug 04, 2026

Q & A: 336 Questions and Answers

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Preparing for the exam will help you screen out questions that are irrelevant for this certification. Ingestion of the data is the most important role in AI. Ready to use the data as soon as possible. Anomaly detection refers to all situations where something out of the ordinary is happening. Accountability models are used for the accuracy rate. Transparency refers to using the data for this service. Interoperability is used on the platform. Microsoft AI-900 exam dumps in order to get the best scores with the Microsoft Azure AI Fundamentals Exam. Tech terms used in AZ-900:Microsoft Azure AI Fundamentals Exam. Serviceidentify is used in the process of AI. Files are used to store the data. The AI application is the product of the AI. Learning is used for this purpose to provide better accuracy rate.

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Requisites of Microsoft AI-900 Exam

In order to take the Microsoft AI-900 exam, you must have a current Azure subscription. You also need a valid Microsoft ID. In addition, be sure to pass the following exams:

  • AZ-100: Fundamentals of Azure
  • AZ-200: Azure Fundamentals Assessment

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

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Microsoft AI-900 中文 Exam Syllabus Topics:

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

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