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Microsoft AI-900 中文 Braindumps - in .pdf Free Demo

  • Exam Code: AI-900-CN
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Last Updated: Aug 26, 2026
  • Q & A: 336 Questions and Answers
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  • Exam Code: AI-900-CN
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Last Updated: Aug 26, 2026
  • Q & A: 336 Questions and Answers
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About Microsoft Azure AI Fundamentals (AI-900中文版) : AI-900 中文 Exam

What is the duration, language, and format of AI-900: Microsoft Azure AI Fundamentals Exam

  • Type of Questions: This test format is multiple choice
  • Length of Examination: 50 mins
  • Passing Score: 70%
  • Number of Questions: 100 to 120 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice)
  • Languages in which this exam is available in: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish

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The Microsoft AI-900 exam, usually known as the Microsoft Azure AI Fundamentals, is well suited to baseline-level IT specialists with knowledge of artificial intelligence (AI) & Machine Learning (ML), and the relevant Microsoft Azure concepts. This is the only test that you should pass to qualify for the Microsoft Certified: Azure AI Fundamentals certification.

Preparation Process

Microsoft offers a wide range of resources to help you prepare for your certification exam. The first step in the preparation process is to go through the topics in detail. This will enable you to understand the specific areas that are covered in the test. With this understanding, you can start to get the materials that will provide more knowledge on the objectives. Thus, Microsoft comes with two training options to help the candidates develop the required skills. These are free online training and instructor-led training.

  • Practice Test: As a future examinee, you also have access to the official practice test to evaluate your understanding of the exam topics before taking the actual test. The link to this training tool can be found on the Microsoft website.
  • Free Online Training: The individuals can explore five free training tutorials that are available on the official exam webpage. They have a series of modules that focus on the specific domains of the test. These training tutorials are recommended for those candidates who are comfortable with the self-paced study. The topics of these manuals include the following options:
    • Get Started with AI on Azure;
    • Create No-Code Predictive Models with Azure ML;
    • Explore NLP;
    • Explore Computer Vision on Microsoft Azure;
    • Explore Conversational Artificial Intelligence.

    The students can find the details of these learning paths on the official website.

  • Instructor-Led Training: The Microsoft Azure AI Fundamentals course is designed to help you gain the required skills to pass the exam and obtain the certification. It introduces the learners to the fundamental concepts of AI and the services available in Microsoft Azure that are useful in creating AI solutions. This training is delivered by the certified partners and its details can be found on the Microsoft website. It is important to mention that this course is designed to be combined with other online materials that are available on the Microsoft Learning platform.

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

Microsoft AI-900 中文 Exam Syllabus Topics:

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

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