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Last Updated: Aug 07, 2026

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About Azure AI Fundamentals Certification and Who It Is Intended for

The Microsoft Certified: Azure AI Fundamentals qualification authenticates the learner's understanding and skills in AI & ML concepts along with associated Azure services. In particular, the individual with this certification is competent in demonstrating their understanding of various workloads related to those terms along with their implementation in Azure cloud computing services. In addition, this certification is an excellent way to get a step ahead in the preparation for other role-based Azure certificates as well as showcasing one's skill in the fundamentals of ML as well as AI. All in all, the Azure AI Fundamentals validation form Microsoft is for beginners and thus, doesn't require any technical knowledge and expertise like, for example, engineering for software. However, some understanding of programming will help you a lot to easily nail test AI-900.

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Prerequisites

This certification test has no official prerequisites. However, the interested candidates must develop their skills and knowledge in the domains of the exam topics. Although the individuals do not need this test to pursue more advanced Azure role-based options, they can gain extensive expertise while preparing for this exam. Your knowledge base can contribute to the success of more advanced certificates such as Microsoft Certified: Azure AI Engineer Associate or Microsoft Certified: Azure Data Scientist Associate.

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

Explain Computer Vision Workloads Features on Azure (15-20%)

Here, the following skills will be measured:

  • Identify Azure services & tools for Computer Vision Projects – This section requires that the learners identify different capabilities of Computer Vision service, Face service, Customer Vision service, and Form Recognizer service.
  • Identify the basic types of Computer Vision Solution – The candidates need to understand and be able to identify a range of features. They include image classification solutions, semantic segmentation solutions, object detection solutions, and optical attributes recognition solutions. It also covers the attributes of facial recognition, facial analysis, and facial detection solutions.

Microsoft AI-900 中文 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Features of generative AI workloads on Azure20–25%- Describe capabilities of Azure OpenAI Service
- Describe generative AI concepts
- Describe responsible AI practices for generative AI
- Describe use cases for generative AI
Topic 2: Artificial Intelligence workloads and considerations15–20%- Identify types of AI workloads
- Describe considerations for developing AI solutions
- Describe responsible AI principles
Topic 3: Features of Natural Language Processing (NLP) workloads on Azure15–20%- Describe capabilities of Azure Language
- Identify types of NLP solutions
- Describe capabilities of Azure Translator
- Describe capabilities of Azure Speech
Topic 4: Fundamental principles of machine learning on Azure15–20%- Describe core concepts of machine learning
- Describe automated machine learning
- Describe machine learning pipelines
- Describe capabilities of Azure Machine Learning
Topic 5: Features of computer vision workloads on Azure15–20%- Describe capabilities of Azure Computer Vision
- Describe capabilities of Azure Custom Vision
- Identify types of computer vision solutions
- Describe capabilities of Azure Face
- Describe capabilities of Azure Form Recognizer
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