Microsoft AI-900 中文 Q&A - in .pdf

  • AI-900 中文 pdf
  • Exam Code: AI-900 中文
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Updated: Aug 08, 2026
  • Q & A: 336 Questions and Answers
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  • Exam Code: AI-900 中文
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
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  • Updated: Aug 08, 2026
  • Q & A: 336 Questions and Answers
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  • AI-900 中文 Testing Engine
  • Exam Code: AI-900 中文
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Updated: Aug 08, 2026
  • Q & A: 336 Questions and Answers
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Exam Details

The Microsoft AI-900 exam is the only qualifying test that leads to the Microsoft Certified: Azure AI Fundamentals certification. It measures one’s knowledge of AI considerations & workloads, features of NLP workloads on Azure, and basic principles of ML on Azure. The candidates can choose to take this exam in English, French, Simplified Chinese, Japanese, German, Spanish, or Korean. It contains 40-60 questions covering different types, including case studies, drag and drop, active screen, build list, and multiple choice. You can schedule your test with Certiport or Pearson VUE. However, it is required to pay the fee of $99 before scheduling it.

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AI-900 中文 Practice Dumps

Skills measured
  • Describe features of conversational AI workloads on Azure (15-20%)
  • Describe fundamental principles of machine learning on Azure (30-35%)
  • Describe AI workloads and considerations (15-20%)
  • Describe features of computer vision workloads on Azure (15-20%)
  • Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)

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
Topic 1: Describe features of Natural Language Processing (NLP) workloads on Azure15-20%- Identify Azure AI services for NLP
- Describe Azure capabilities for NLP
- Identify common NLP tasks
Topic 2: Describe features of computer vision workloads on Azure15-20%- Identify common computer vision tasks
- Identify Azure AI services for computer vision
- Describe Azure capabilities for computer vision
Topic 3: Describe AI workloads and considerations15-20%- Identify features of common AI workloads
- Identify guiding principles for responsible AI
Topic 4: Describe fundamental principles of machine learning on Azure30-35%- Describe core machine learning concepts
- Describe features of no-code automated ML
- Identify common machine learning tasks
- Describe Azure Machine Learning capabilities
Topic 5: Describe features of Generative AI workloads on Azure15-20%- Describe Azure OpenAI Service capabilities
- Describe generative AI concepts
- Identify responsible AI considerations for generative AI
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