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

AI-900 中文 testking pdf

Exam Code: AI-900-CN

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

Updated: Jul 23, 2026

Q & A: 336 Questions and Answers

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

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This certificate is an opportunity for candidates to showcase their mastery of the Machine Learning (ML) and Artificial Intelligence (AI) workloads and their implementation of Azure services. For that reason, AI-900 exam can be taken by all candidates from technical and non-technical fields. While software engineering and data science skills may not be required for such an evaluation, it is important to have general programming knowledge to stand a chance of cracking this test right away. By and large, the updated Microsoft Certified: Azure AI Fundamentals designation can help you advance your career growth by preparing you for advanced Azure role-based certifications including the Microsoft Certified: Azure AI Engineer Associate and the Microsoft Certified: Azure Data Scientist Associate certificates.

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Microsoft AI-900 中文 Exam Syllabus Topics:

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

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