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Microsoft Microsoft Certified: Azure AI Fundamentals AI-900-CN

AI-900-CN

Exam Code: AI-900-CN

Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)

Updated: Sep 03, 2026

Q & A: 336 Questions and Answers

AI-900-CN Free Demo download:

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IT-Tests AI-900 中文 Exam Features

Who should take the AI-900: Microsoft Azure AI Fundamentals Exam

High level of difficulty and many challenging questions. Identify the different types of AI models. AI design choosing tools. Who should take the exam? Artificial intelligence. Describe the strengths and weaknesses for artificial intelligence.

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

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The Importance of Microsoft AI-900 Exam

Microsoft AI-900 exam is an associate level certification which is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017. Role of Azure Intelligent Solutions. Windows 2012, Windows 2016, and SQL Server 2017. .NET Framework 4.6.1 (or 4.7), or higher. Resident Deployment of the Solutions. Classify application workloads. Apply Azure monitoring and analytics, Operations Management Suite (OMS) logs, and Event Hubs. Manage the master database. Implement master database failover. Microsoft AI-900 exam dumps aligns with the objectives listed below. Classify application workloads. Deploy, configure, set up, activate, maintain, troubleshoot and support all necessary Azure services. Manage the master database.

Informationidentify the load of a given server. Forums and blogs about Azure and use of its products. Long term planning and development of future plans. Categoriesidentify the Azure deployment models. Forums and blogs about Azure and use of its products. Easy management of the Azure resources. Responsible for managing the database when the system doesn't work normally. Array of Solutionstests the knowledge of the candidate. Backgrounds of the candidate before they start their work. Push when you are in the process of testing.

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How to Prepare For AI-900: Microsoft Azure AI Fundamentals

Preparation Guide for AI-900: Microsoft Azure AI Fundamentals

Introduction

Microsoft AI-900 exam is designed for Microsoft partners who are certified by Microsoft to integrate Microsoft Azure Intelligent Solutions into their own products and solutions. The objective of the certification is to verify that approved partners have the knowledge and skills to deploy, configure, set up, activate, maintain, troubleshoot, and support all necessary Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam taker level of competence in the functions, features, and services of Azure. The Microsoft AI-900 Certification Exam is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017, and NET Framework. Courses are available online or in-person depending on individual needs.

This article will cover the areas of knowledge required for this exam, how many questions are covered in each area, and who is taking this certification exam.

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Microsoft AI-900 中文 Exam Syllabus Topics:

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

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