Microsoft AI-900 中文 Exam Information and Actual Questions

  • Exam Code/Number: AI-900 中文
  • Exam Name/Title: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Certification Provider: Microsoft
  • Corresponding Certification: Microsoft Certified: Azure AI Fundamentals
  • Exam Questions: 336
  • Updated On: Jun 24, 2026

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

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All the information you need to pass Microsoft Azure AI Fundamentals (AI-900中文版) AI-900 中文 exam and free practice exam verified by ExamDiscuss exam experts.

Microsoft AI-900 中文 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Exam AI-900: Microsoft Azure AI Fundamentals
Exam Number:AI-900
Exam Format:Multiple choice (single answer), Multiple response (multiple answers), Drag-and-drop, Hot area, Scenario-based case studies, True/false
Passing Score:700 (Scaled 1–1000)
Exam Duration:60 minutes
Certificate Validity Period:Lifetime (Does not expire)
Available Languages:English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Russian, Indonesian, Arabic (Saudi Arabia), Chinese (Traditional), Italian
Exam Price:$99 USD
Real Exam Qty:40–60
Related Certifications:Microsoft Certified: Azure AI Engineer Associate
Microsoft Certified: Azure Data Scientist Associate
Microsoft Certified: Azure Fundamentals (AZ-900)
Sample Questions:Microsoft AI-900 中文 Sample Questions
Exam Way:Online proctored remote exam or onsite testing at Pearson VUE authorized centers
Pre Condition:No mandatory prerequisites; basic cloud computing knowledge is recommended
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900/

Microsoft AI-900 exam is divided into various sections that cover different aspects of AI and Azure. These sections include understanding AI workloads and considerations, understanding fundamental principles of machine learning on Azure, and exploring various AI services and their applications on Azure.

Microsoft AI-900 中文 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Describe features of generative AI workloads on Azure: Features of generative AI solutions and capabilities of Azure OpenAI Service are discussed in this topic.
Topic 2
  • Describe features of computer vision workloads on Azure: This topic discusses identifying common types of computer vision solution, Azure tools and services for computer vision tasks.
Topic 3
  • Describe fundamental principles of machine learning on Azure: It describes core machine learning concepts and Azure Machine Learning capabilities. Moreover, the topic also delves into identifying common machine-learning techniques.
Topic 4
  • Describe features of Natural Language Processing (NLP) workloads on Azure: In this topic, questions about common NLP Workload Scenarios features, Azure tools, and services for NLP workloads appear.
Topic 5
  • Describe Artificial Intelligence workloads and considerations: It identifies specifications of common AI workloads and guiding principles for responsible AI.

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

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 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.
  • 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.


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