Microsoft AI-900 中文 valid study dumps : Microsoft Azure AI Fundamentals (AI-900中文版)

  • Exam Code: AI-900-CN
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900中文版)
  • Updated: Aug 15, 2026
  • Q&As: 336 Questions and Answers

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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.

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

Describe NLP Workloads Features on Azure (15-20%)

This domain contains the following details that you need to learn about:

  • Identify the features of basic NLP (Natural Language Processing) Workload Scenarios – The individuals should be able to identify various uses and features of various components, for example, keyphrase extraction, sentiment analysis, entity recognition, translation, language modeling, and speech recognition & synthesis.
  • Identify Azure services & tools for Natural Language Processing Workloads – This topic is created to equip you with the ability to identify various capabilities, such as Speech service, Text Analytics service, Translator Text service, and Language Understanding service.

Important facts you need to know about AI-900: Microsoft Azure AI Fundamentals Exam

Preparing for the exam will help you screen out questions that are irrelevant for this certification. Ingestion of the data is the most important role in AI. Ready to use the data as soon as possible. Anomaly detection refers to all situations where something out of the ordinary is happening. Accountability models are used for the accuracy rate. Transparency refers to using the data for this service. Interoperability is used on the platform. Microsoft AI-900 exam dumps in order to get the best scores with the Microsoft Azure AI Fundamentals Exam. Tech terms used in AZ-900:Microsoft Azure AI Fundamentals Exam. Serviceidentify is used in the process of AI. Files are used to store the data. The AI application is the product of the AI. Learning is used for this purpose to provide better accuracy rate.

Concepts of the AI are explained in the Microsoft AI-900 exam. Image classification is used as the labeling. Recommendation engine is used as the indexing. Intelligent chatbots are used as the chatbot. Community engagement is the chatbot. Custom bot is used as the chatbot. Extracts are used for this purpose. Brainpool is the tool used to perform the extraction. Word embedding is used as the vector training. Dimensionality reduction is used for this purpose. Intelligent chatbot are used as the chatbot.

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Microsoft AI-900 中文 Exam Syllabus Topics:

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

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