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Microsoft AI-900 Exam Syllabus Topics:

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

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                      Microsoft Azure AI Fundamentals Sample Questions (Q27-Q32):

                      NEW QUESTION # 27
                      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:

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


                      NEW QUESTION # 28
                      To complete the sentence, select the appropriate option in the answer area.

                      Answer:

                      Explanation:

                      Reference:
                      https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles AI systems should perform reliably and safely. For example, consider an AI-based software system for an autonomous vehicle; or a machine learning model that diagnoses patient symptoms and recommends prescriptions. Unreliability in these kinds of system can result in substantial risk to human life.
                      https://docs.microsoft.com/en-us/learn/modules/get-started-ai-fundamentals/7-understand-responsible-ai


                      NEW QUESTION # 29
                      Select the answer that correctly completes the sentence.

                      Answer:

                      Explanation:

                      Explanation:

                      This question refers to a system that monitors a user's emotions or expressions-in this case, identifying whether a kiosk user is annoyed-through a video feed. According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify Azure services for computer vision," this scenario falls under facial analysis, which is a capability of Azure AI Vision or the Face API.
                      Facial analysis involves detecting human faces in images or video and analyzing facial features to interpret emotions, expressions, age, gender, or facial landmarks. The AI model does not try to identify who the person is but rather interprets how they appear or feel. For example, facial analysis can detect emotions such as happiness, anger, sadness, or surprise, which allows applications to infer a user's engagement or frustration level while interacting with a system.
                      Option review:
                      * Face detection: Identifies the presence and location of a face in an image but does not interpret expressions or emotions.
                      * Facial recognition: Matches a detected face to a known individual's identity (for authentication or security), not for emotion detection.
                      * Optical character recognition (OCR): Extracts text from images or scanned documents and has no relation to human emotion or facial features.
                      Therefore, determining whether a kiosk user is annoyed, happy, or frustrated involves emotion detection within facial analysis, making Facial analysis the correct answer.
                      This aligns with AI-900's definition of computer vision workloads, where facial analysis provides insights into emotions and expressions, supporting user experience optimization and customer behavior analytics.


                      NEW QUESTION # 30
                      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:

                      Reference:
                      https://docs.microsoft.com/en-us/azure/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.0


                      NEW QUESTION # 31
                      You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
                      Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.

                      Answer:

                      Explanation:

                      Explanation
                      Graphical user interface, text, application, chat or text message Description automatically generated

                      Reference:
                      https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines


                      NEW QUESTION # 32
                      ......

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