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Microsoft AI-900 Exam Syllabus Topics:

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

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                      Microsoft Azure AI Fundamentals Sample Questions (Q124-Q129):

                      NEW QUESTION # 124
                      For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

                      Answer:

                      Explanation:

                      Explanation


                      NEW QUESTION # 125
                      To complete the sentence, select the appropriate option in the answer area.

                      Answer:

                      Explanation:

                      Reference:
                      https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai


                      NEW QUESTION # 126
                      Select the answer that correctly completes the sentence.

                      Answer:

                      Explanation:

                      Explanation


                      NEW QUESTION # 127
                      Select the answer that correctly completes the sentence.

                      Answer:

                      Explanation:

                      Explanation:

                      This question is drawn from the Microsoft Azure AI Fundamentals (AI-900) syllabus section "Describe features of natural language processing (NLP) workloads on Azure." According to the Microsoft Learn materials, Natural Language Processing (NLP) is a branch of artificial intelligence that allows computers to analyze, understand, and generate human language. NLP enables machines to work with text or speech data in a way that extracts meaning, sentiment, and intent.
                      Microsoft defines NLP as enabling scenarios such as language detection, text classification, key phrase extraction, sentiment analysis, and named entity recognition. The example given-classifying emails as
                      "work-related" or "personal"-is a text classification task, which falls under NLP capabilities. The AI model processes the textual content of emails, identifies linguistic patterns, and categorizes them based on the detected topic or context.
                      Let's analyze the other options:
                      * Predict the number of future car rentals # This is a forecasting task, handled by machine learning regression models, not NLP.
                      * Predict which website visitors will make a transaction # This is a classification or prediction problem in machine learning, not NLP, since it deals with behavioral or numerical data rather than language.
                      * Stop a process in a factory when extremely high temperatures are registered # This is an IoT or anomaly detection scenario, focusing on sensor data, not language understanding.
                      Therefore, only classifying email messages as work-related or personal correctly represents an NLP use case.
                      It illustrates how NLP can analyze written text and make intelligent categorizations-a key capability covered in AI-900's natural language workloads section.


                      NEW QUESTION # 128
                      For each of the following statements, select Yes if the statement is true. Otherwise, select No.
                      NOTE: Each correct selection is worth one point.

                      Answer:

                      Explanation:

                      Explanation

                      Reference:
                      https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/get-started-build-detector


                      NEW QUESTION # 129
                      ......

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