Microsoft AI-900J exam dumps : Microsoft Azure AI Fundamentals (AI-900日本語版)

  • Exam Code: AI-900J
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900日本語版)
  • Updated: Oct 08, 2026     Q & A: 336 Questions and Answers

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What is the duration, language, and format of AI-900: Microsoft Azure AI Fundamentals Exam

  • Type of Questions: This test format is multiple choice
  • Languages in which this exam is available in: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish
  • Passing Score: 70%
  • Length of Examination: 50 mins
  • Number of Questions: 100 to 120 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice)

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

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One groundbreaking tool for the past decade or so has been Artificial Intelligence (AI). And it feels good to see top-ranked companies and IT certification vendors such as Microsoft coming to the fore to help fast-track the latest developments around this field. One of the outstanding designations today is the Microsoft Certified: Azure AI Fundamentals, which is well suited to all trainees who are making their first steps in this sector. With the latest technologies, the demand for AI engineers is at an all-time high, with industry experts stating that the trend could go on for many years into the future. This could only mean one thing: now is the perfect time to get into this field. The Microsoft AI-900 exam with an updated curriculum will help you make a strong statement in this area so you’ll manage to focus on more advanced certifications at a later stage of your career. So, get started with the above-mentioned resources and become the best specialist you can be to reach the optimum heights in your professional life.

Microsoft AI-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
  • 1. Sentiment analysis
    • 2. Key phrase extraction
      • 3. Language modeling and translation
        Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
        • 1. Training and validation concepts
          • 2. Supervised vs unsupervised learning
            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. Image classification
                  • 2. OCR and image analysis
                    • 3. Object detection

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