Microsoft AI-900 : Microsoft Azure AI Fundamentals

Exam Code: AI-900

Exam Name: Microsoft Azure AI Fundamentals

Updated: Aug 20, 2026

Q & A: 336 Questions and Answers

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

Here, the following skills will be measured:

  • 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.
  • 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.

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

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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Microsoft AI-900 Exam Syllabus Topics:

SectionWeightObjectives
Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
  • 1. Common AI workloads
    • 2. Responsible AI principles
      Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
      • 1. Supervised vs unsupervised learning
        • 2. Training and validation concepts
          Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
          • 1. Language modeling and translation
            • 2. Sentiment analysis
              • 3. Key phrase extraction
                Features of computer vision workloads on Azure15-20%- Computer vision solutions
                • 1. OCR and image analysis
                  • 2. Object detection
                    • 3. Image classification

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