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Microsoft AI-300 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement generative AI quality assurance and observability10–15%- Evaluate and test generative AI applications
  • 1. Define evaluation metrics and criteria
    • 2. Test for safety, accuracy, and relevance
      - Monitor generative AI systems
      • 1. Track usage, performance, and errors
        • 2. Implement logging and alerting
          Topic 2: Design and implement an MLOps infrastructure15–20%- Implement infrastructure as code for Machine Learning
          • 1. Automate infrastructure provisioning
            • 2. Use Bicep or Azure CLI to deploy resources
              - Create and manage Machine Learning workspace resources and assets
              • 1. Configure workspace settings and security
                • 2. Manage compute targets, datastores, and environments
                  Topic 3: Design and implement a GenAIOps infrastructure20–25%- Set up Microsoft Foundry environment
                  • 1. Configure projects, connections, and security
                    • 2. Manage compute and deployment resources
                      - Implement infrastructure for generative AI workloads
                      • 1. Design scalable and secure architecture
                        • 2. Integrate with Azure services and tools
                          Topic 4: Optimize generative AI systems and model performance15–20%- Improve efficiency and cost-effectiveness
                          • 1. Optimize inference and deployment
                            • 2. Manage resource utilization
                              - Optimize model selection and configuration
                              • 1. Tune prompts and generation settings
                                • 2. Choose appropriate models and parameters
                                  Topic 5: Implement machine learning model lifecycle and operations25–30%- Deploy models to production
                                  • 1. Deploy to real-time and batch endpoints
                                    • 2. Configure deployment options and scaling
                                      - Orchestrate model training and experimentation
                                      • 1. Create and manage pipelines
                                        • 2. Track experiments and metrics
                                          - Monitor and maintain models in production
                                          • 1. Implement retraining and update workflows
                                            • 2. Monitor data and model drift
                                              - Register, version, and package models
                                              • 1. Create reusable model packages
                                                • 2. Manage model registry

                                                  Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

                                                  1. Drag and Drop Question
                                                  A team deploys a classification model to production and monitors performance and data changes.
                                                  The team wants to ensure that significant drops in prediction accuracy automatically trigger the following:
                                                  - Stakeholders must be notified of the drops.
                                                  - Retraining must be initiated when thresholds are exceeded
                                                  You need to configure monitoring to meet the requirements.
                                                  Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


                                                  2. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
                                                  After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
                                                  You work in Microsoft Foundry with a prompt flow.
                                                  You must manually evaluate prompts and compare results across prompt variants.
                                                  You need to capture the inputs, outputs, token usage, and latencies for each flow run for the evaluation.
                                                  Solution: Create prompt variants and compare their outputs in the Evaluation experience.
                                                  Does the solution meet the goal?

                                                  A) Yes
                                                  B) No


                                                  3. Drag and Drop Question
                                                  A team is deploying a new version of a customer scoring model to a production online endpoint in Azure Machine Learning.
                                                  The team must minimize risk by gradually introducing the new model version and ensuring that traffic can be reverted immediately if issues occur.
                                                  You need to roll out the new model according to the requirements.
                                                  Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


                                                  4. Drag and Drop Question
                                                  A customer-facing web application uses a foundational model deployed through Microsoft Foundry.
                                                  A new model version must be introduced and validated without disrupting production traffic.
                                                  You need to deploy the new version by using a safe promotion strategy.
                                                  Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


                                                  5. DRAG DROP
                                                  A team deploys a classification model to production and scores incoming customer data daily.
                                                  After several weeks, business stakeholders report unexpected changes in prediction behavior, even though the endpoint remains healthy.
                                                  You need to determine whether data drift is occurring and if it is, identify the appropriate actions.
                                                  Which action should you perform for each observed signal? To answer, move the appropriate actions to the correct observed signals. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
                                                  NOTE: Each correct selection is worth one point.


                                                  Solutions:

                                                  Question # 1
                                                  Answer: Only visible for members
                                                  Question # 2
                                                  Answer: B
                                                  Question # 3
                                                  Answer: Only visible for members
                                                  Question # 4
                                                  Answer: Only visible for members
                                                  Question # 5
                                                  Answer: Only visible for members

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