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Microsoft AI-900 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
  • 1. Supervised vs unsupervised learning
    • 2. Training and validation concepts
      Topic 2: Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
      • 1. Key phrase extraction
        • 2. Language modeling and translation
          • 3. Sentiment analysis
            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 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 (Q309-Q314):

                      NEW QUESTION # 309
                      Which Azure Al Language feature can be used to retrieve data, such as dates and people's names, from social media posts?

                      Answer: D

                      Explanation:
                      The Azure AI Language service provides several NLP features, including language detection, key phrase extraction, sentiment analysis, and named entity recognition (NER).
                      When you need to extract specific data points such as dates, names, organizations, or locations from unstructured text (for example, social media posts), the correct feature is Entity Recognition.
                      Entity Recognition identifies and classifies information in text into predefined categories like:
                      * Person names (e.g., "John Smith")
                      * Organizations (e.g., "Contoso Ltd.")
                      * Dates and times (e.g., "October 22, 2025")
                      * Locations, events, and quantities
                      This capability helps transform unstructured textual data into structured data that can be analyzed or stored.
                      Option analysis:
                      * A (Language detection): Determines the language of a text (e.g., English, French).
                      * B (Speech recognition): Converts spoken audio to text; not applicable here.
                      * C (Key phrase extraction): Identifies important phrases or topics but not specific entities like names or dates.
                      * D (Entity recognition): Correctly extracts names, dates, and other specific data from text.
                      Hence, the accurate feature for this scenario is D. Entity Recognition.


                      NEW QUESTION # 310
                      You ate building a Conversational Language Understanding model for an e-commerce business.
                      You need to ensure that the model detects when utterances are outside the intended scope of the model.
                      What should you do?

                      Answer: A


                      NEW QUESTION # 311
                      Select the answer that correctly completes the sentence

                      Answer:

                      Explanation:


                      NEW QUESTION # 312
                      Match the facial recognition tasks to the appropriate questions.
                      To answer, drag the appropriate task from the column on the left to its question 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://azure.microsoft.com/en-us/services/cognitive-services/face/#features


                      NEW QUESTION # 313
                      For a machine learning progress, how should you split data for training and evaluation?

                      Answer: B

                      Explanation:
                      https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/split-data


                      NEW QUESTION # 314
                      ......

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