Microsoft AI-900 中文 dumps - 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 01, 2026
  • Q & A: 336 Questions and Answers
  • PDF Price: $69.99
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  • Exam Code: AI-900 中文
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Updated: Aug 01, 2026
  • Q & A: 336 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft AI-900 中文 dumps - Testing Engine

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 01, 2026
  • Q & A: 336 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

About Microsoft AI-900 中文 Exam Braindumps

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The Microsoft AI-900 exam is designed for those individuals who have little to no experience in the world of IT. It is aimed at the students with both non-technical and technical backgrounds. They have basic programming experience and knowledge. However, they are not required to have software engineering or data science experience.

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AI-900 中文 exam dumps

Skills measured

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

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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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Prerequisites

Microsoft AI-900 is a foundational-level certification exam. Therefore, the potential candidates are required to possess basic knowledge of the AI and ML concepts. They also need to have an understanding of the associated Microsoft Azure services. These individuals can have technical or non-technical backgrounds. They do not need to have software engineering or science experience before taking the test. However, some programming experience or knowledge would be an advantage for them.

The AI-900 exam is designed to validate the students’ knowledge of AI workloads & considerations, as well as attributes of computer vision workloads within Azure. It also certifies their understanding of the basic principles of ML on Azure and attributes of conversational Artificial Intelligence workloads on Azure. The applicants are also required to demonstrate their knowledge of the attributes of NLP (Natural Language Processing) workloads on Azure.

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

Microsoft AI-900 中文 Exam Syllabus Topics:

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

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