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  • Exam Code: AI-900 中文
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Updated: Sep 16, 2026
  • Q & A: 336 Questions and Answers
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  • Exam Code: AI-900 中文
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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The technologies that are tested on Microsoft AI-900 exam are necessary to develop intelligent operations based on cloud computing. Audience for this certification exam is individuals who work as computer programmers, developers, system administrators and project managers. Built for high-volume, high-speed web applications that use Azure, this Examines the skills required to develop intelligent cloud solutions. Smarter IT environments are the goal of this exam. Single sign-on for Azure, is an exam objective. Microsoft AI-900 exam dumps helps to make it easier for students to get this certification. Outline the business value of the exam. The importance of having this certification. Identify the technologies covered on Microsoft AI-900 exam. Gain a better understanding of the skills you'll need to develop intelligent cloud solutions.

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Microsoft Azure AI Fundamentals Exam Certification Details:

Sample QuestionsMicrosoft Azure AI Fundamentals Sample Questions
Duration60 mins
Number of Questions40-60
Exam NameMicrosoft Certified - Azure AI Fundamentals
Exam CodeAI-900
Schedule ExamPearson VUE
Passing Score700 / 1000
Exam Price$99 (USD)
Books / TrainingCourse AI-900T00: Microsoft Azure AI Fundamentals

Schedule exam

Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian

Retirement date: none

Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.

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Microsoft AI-900 中文 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Features of computer vision workloads on Azure15-20%- Computer vision solutions
  • 1. Object detection
    • 2. Image classification
      • 3. OCR and image analysis
        Topic 2: Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
        • 1. Language modeling and translation
          • 2. Sentiment analysis
            • 3. Key phrase extraction
              Topic 3: Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
              • 1. Training and validation concepts
                • 2. Supervised vs unsupervised learning
                  Topic 4: Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
                  • 1. Responsible AI principles
                    • 2. Common AI workloads

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