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AI-900 exam dumps

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  • Exam Code: AI-900
  • Exam Name: Microsoft Azure AI Fundamentals
  • No. of Questions: 336 Questions and Answers
  • Updated: Sep 04, 2026

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Career Opportunities

The individuals can pursue a lot of career opportunities with a Microsoft certificate. The Microsoft Certified: Azure AI Fundamentals certification is not an exception. Although it is a foundational-level path, the certificate holders can start their careers on a good footing. Some of the job titles that these entry-level professionals can apply for include an Azure Data Scientist, an Azure AI Engineer, an Azure Administrator, an Azure Developer, an Azure Solution Architect, and an Azure DevOps Engineer. For these positions, the applicants can expect to earn an average of $80,000 per annum.

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

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Target Audience

The Microsoft AI-900 exam is designed for those individuals who have little to no experience in the world of IT. It is aimed at the students with both non-technical and technical backgrounds. They have basic programming experience and knowledge. However, they are not required to have software engineering or data science experience.

Microsoft AI-900 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
  • 1. Supervised vs unsupervised learning
    • 2. Training and validation concepts
      Topic 2: Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
      • 1. Key phrase extraction
        • 2. Language modeling and translation
          • 3. Sentiment analysis
            Topic 3: Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
            • 1. Common AI workloads
              • 2. Responsible AI principles
                Topic 4: Features of computer vision workloads on Azure15-20%- Computer vision solutions
                • 1. Image classification
                  • 2. Object detection
                    • 3. OCR and image analysis

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