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Microsoft AI-900 Exam Syllabus Topics:

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

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                      Microsoft Azure AI Fundamentals Sample Questions (Q138-Q143):

                      NEW QUESTION # 138
                      To complete the sentence, select the appropriate option in the answer area.

                      Answer:

                      Explanation:

                      Reference:
                      https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and-manage-intelligent-bots


                      NEW QUESTION # 139
                      Match the types of natural languages processing workloads to the appropriate scenarios.
                      To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
                      NOTE: Each correct selection is worth one point.

                      Answer:

                      Explanation:

                      Reference:
                      https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics


                      NEW QUESTION # 140
                      You need to identify street names based on street signs in photographs.
                      Which type of computer vision should you use?

                      Answer: A


                      NEW QUESTION # 141
                      To complete the sentence, select the appropriate option in the answer area.
                      Using Recency, Frequency, and Monetary (RFM) values to identify segments of a customer base is an example of___________

                      Answer: A

                      Explanation:
                      Classification


                      NEW QUESTION # 142
                      Match the machine learning tasks to the appropriate scenarios.
                      To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
                      NOTE: Each correct selection is worth one point.

                      Answer:

                      Explanation:

                      Reference:
                      https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
                      https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml


                      NEW QUESTION # 143
                      ......

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