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Learning Path

All in all, Microsoft provides two ways to help candidates prepare for the Microsoft AI-900 exam. These include the free online learning option and the paid, instructor-led training. Let’s discuss the two most popular courses offered by each of these options by the vendor:

  • Microsoft Azure AI Fundamentals

    This one-day course is part of the instructor-led learning platform and is, therefore, a paid option. As the name suggests, it is meant to introduce the candidates to fundamental AI concepts. The training, in particular, emphasizes the skills you need to become well versed in AI workloads and understand the Azure services that support such solutions. Usually, the course curriculum is viewed as comprehensive blended learning, featuring a combination of online materials and instructor-led training to ensure candidates have a good grasp of the exam topic areas. Even more, the hands-on exercises that are featured here are meant to help learners understand the test domains in real-world scenarios. Familiarity with the internet and computer technology is not a prerequisite but a great combination that will go a long way toward helping you register excellent results in this course and the ultimate exam.

  • Get Started with Artificial Intelligence

    The online gratis class, “Get Started with Artificial Intelligence” features one module and is intended to run for a maximum of 34 minutes. In general, this course is designed to help you get started with Microsoft services that empower new AI solutions. There are no prerequisites associated with this training. However, it features one module with a total of 10 units including the introduction and an understanding of machine learning, anomaly detection, computer vision, natural language processing, conversational AI, and responsible AI just to mention a few. Visit the official certification page to find out more information about this learning path that also includes classes on ML, NLP, and conversational AI.

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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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Certification Topics of Microsoft AI-900 Exam

Our Microsoft AI-900 exam dumps covers the following objectives of Microsoft AI-900 Exam.

  • Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
  • Describe fundamental principles of machine learning on Azure (30-35%)
  • Describe features of conversational AI workloads on Azure (15-20%)
  • Describe features of computer vision workloads on Azure (15-20%)
  • Describe AI workloads and considerations (15-20%)

Requisites of Microsoft AI-900 Exam

In order to take the Microsoft AI-900 exam, you must have a current Azure subscription. You also need a valid Microsoft ID. In addition, be sure to pass the following exams:

  • AZ-200: Azure Fundamentals Assessment
  • AZ-100: Fundamentals of Azure

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

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Microsoft AI-900 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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
        Topic 2: Features of computer vision workloads on Azure15-20%- Computer vision solutions
        • 1. OCR and image analysis
          • 2. Object detection
            • 3. Image classification
              Topic 3: Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
              • 1. Responsible AI principles
                • 2. Common AI workloads
                  Topic 4: Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
                  • 1. Training and validation concepts
                    • 2. Supervised vs unsupervised learning

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