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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.

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Exam Overview

This certification test is available in English, Spanish, Simplified Chinese, Japanese, French, Korean, and German. You will find different formats of questions while dealing with this Microsoft exam. These include multiple choice, drag and drop, build list, active screen, short answer, and best answer. The test costs $99 and the learners can register for it through Pearson VUE or Certiport.

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.

Describing AI-900 Exam Facts and Topics

In general, AI-900 is a computer-based exam that’s available in English, Chinese, Japanese, Spanish, French, German, and Korean languages. It costs $99 for every attempt and can be scheduled with Certiport or Pearson VUE. Recently, the AI-900 exam curriculum has been updated to reflect the following skills as contained in the official study guide:

  • Designing features of NLP (Natural Language Processing) workloads on Azure (15-20%);
  • Detailing Artificial Intelligence considerations and workloads (15-20%);
  • Defining features of conversational AI workloads on Azure (15-20%).
  • Describing fundamental principles of machine learning on Azure (30-35%);
  • Explaining features of computer vision workloads on Azure (15-20%);

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Microsoft AI-900 Korean Exam Syllabus Topics:

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

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