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Microsoft AI-900 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
  • 1. Responsible AI principles
    • 2. Common AI workloads
      Topic 2: Features of computer vision workloads on Azure15-20%- Computer vision solutions
      • 1. Image classification
        • 2. Object detection
          • 3. OCR and image analysis
            Topic 3: 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
                  Topic 4: Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
                  • 1. Supervised vs unsupervised learning
                    • 2. Training and validation concepts

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                      Microsoft Azure AI Fundamentals Sample Questions (Q321-Q326):

                      NEW QUESTION # 321
                      Match the services to the appropriate descriptions.
                      To answer, drag the appropriate service from the column on the left to its description on the right. Each service may be used once, more than once, or not at all.
                      NOTE: Each correct match is worth one point

                      Answer:

                      Explanation:

                      Explanation
                      Graphical user interface, application Description automatically generated.


                      NEW QUESTION # 322
                      To complete the sentence, select the appropriate option in the answer area.

                      Answer:

                      Explanation:

                      Explanation

                      With Microsoft's Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack, and more.
                      Reference:
                      https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and


                      NEW QUESTION # 323
                      Match the types of computer vision 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:

                      Explanation
                      Box 1: Facial recognition
                      Face detection that perceives faces and attributes in an image; person identification that matches an individual in your private repository of up to 1 million people; perceived emotion recognition that detects a range of facial expressions like happiness, contempt, neutrality, and fear; and recognition and grouping of similar faces in images.
                      Box 2: OCR
                      Box 3: Objection detection
                      Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
                      The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like
                      "indoor", which can't be localized with bounding boxes.
                      Reference:
                      https://azure.microsoft.com/en-us/services/cognitive-services/face/
                      https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection


                      NEW QUESTION # 324
                      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://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features


                      NEW QUESTION # 325
                      Select the answer that correctly completes the sentence.

                      Answer:

                      Explanation:

                      Explanation:


                      NEW QUESTION # 326
                      ......

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