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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
      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
            Features of computer vision workloads on Azure15-20%- Computer vision solutions
            • 1. Image classification
              • 2. Object detection
                • 3. OCR and image analysis
                  Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
                  • 1. Training and validation concepts
                    • 2. Supervised vs unsupervised learning

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                      Microsoft Azure AI Fundamentals Sample Questions (Q327-Q332):

                      NEW QUESTION # 327
                      You build a machine learning model by using the automated machine learning user interface (UI).
                      You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
                      What should you do?

                      Answer: A

                      Explanation:
                      Model Explain Ability.
                      Most businesses run on trust and being able to open the ML "black box" helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
                      Reference:
                      https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning


                      NEW QUESTION # 328
                      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-gb/azure/cognitive-services/text-analytics/overview
                      https://azure.microsoft.com/en-gb/services/cognitive-services/speech-services/ You can use the Speech service to transcribe a call to text - Yes we can use Speech to Text API to achieve this
                      https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction You can use a speech service to translate the audio of a call to a different language - Yes we can use Speech translation service to achieve this The Speech service includes the following application programming interfaces (APIs):
                      Speech-to-text - used to transcribe speech from an audio source to text format.
                      Text-to-speech - used to generate spoken audio from a text source.
                      Speech Translation - used to translate speech in one language to text or speech in another.
                      https://docs.microsoft.com/en-us/learn/modules/translate-text-with-translation-service/2-get-started-azure You can use text analytics service to extract key entities from a call transcript -Yes Text Analytics API helps to achieve this
                      https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure


                      NEW QUESTION # 329
                      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/es-es/blog/machine-assisted-text-classification-on-content-moderator-public-preview/
                      https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing


                      NEW QUESTION # 330
                      To complete the sentence, select the appropriate option in the answer area.

                      Answer:

                      Explanation:

                      Reference:
                      https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features


                      NEW QUESTION # 331
                      You are processing photos of runners in a race.
                      You need to read the numbers on the runners' shirts to identify the runners in the photos. Which type of computer vision should you use?

                      Answer: D


                      NEW QUESTION # 332
                      ......

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