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Microsoft AI-300 Exam Syllabus Topics:

SectionObjectives
Topic 1: Design and implement generative AI solutions- RAG (Retrieval Augmented Generation) solutions
  • 1. Vector search integration
    • 2. Knowledge grounding and retrieval design
      - Large language model integration
      • 1. Use Azure OpenAI Service capabilities
        • 2. Prompt engineering and prompt flow design
          Topic 2: Operationalizing machine learning solutions- Deployment and monitoring
          • 1. Monitor performance and drift
            • 2. Deploy models to endpoints
              - ML lifecycle management
              • 1. Model versioning and registry usage
                • 2. Model training and evaluation in Azure Machine Learning
                  Topic 3: Implement secure and scalable AI systems- Scalability and performance optimization
                  • 1. Cost optimization strategies
                    • 2. Autoscaling AI workloads
                      - Security and governance
                      • 1. Data privacy and compliance considerations
                        • 2. Identity and access management for AI services
                          Topic 4: Plan and design AI solutions using Azure AI services- Responsible AI design
                          • 1. Fairness, transparency, and accountability considerations
                            • 2. Responsible AI mitigation strategies
                              - Requirements gathering and solution architecture
                              • 1. Identify business requirements for AI solutions
                                • 2. Select appropriate Azure AI services

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                                  Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions (Q182-Q187):

                                  NEW QUESTION # 182
                                  You create an Azure Machine Learning workspace.
                                  You plan to write an Azure Machine Learning SDK for Python v2 script that logs an image for an experiment.
                                  The logged image must be available from the images tab in Azure Machine Learning Studio.
                                  You need to complete the script.
                                  Which code segments should you use? To answer, select the appropriate options in the answer area.
                                  NOTE: Each correct selection is worth one point.

                                  Answer:

                                  Explanation:

                                  Explanation:


                                  NEW QUESTION # 183
                                  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 in the review screen.
                                  You train and register an Azure Machine Learning model.
                                  You plan to deploy the model to an online endpoint.
                                  You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.
                                  Solution:
                                  Create a managed online endpoint and set the value of its auto_mode parameter to key. Deploy the model to the inline endpoint.
                                  Does the solution meet the goal?

                                  Answer: A


                                  NEW QUESTION # 184
                                  You manage an Azure Machine Learning workspace by using the Azure CLI ml extension v2. You need to define a YAML schema to create a compute cluster. Which schema should you use?

                                  Answer: B


                                  NEW QUESTION # 185
                                  Hotspot Question
                                  You manage an Azure Machine Learning workspace named workspace1.
                                  You must register an Azure Blob storage datastore in workspace1 by using an access key. You develop Python SDK v2 code to import all modules required to register the datastore.
                                  You need to complete the Python SDK v2 code to define the datastore.
                                  How should you complete the code? To answer, select the appropriate options in the answer area.
                                  NOTE: Each correct selection is worth one point.

                                  Answer:

                                  Explanation:

                                  Explanation:
                                  How should you complete the code?
                                  Box 1: container_name
                                  container_name specifies the parameter name used in the AzureBlobDatastore constructor to identify your target blob storage container.
                                  Box 2: wasbs
                                  Correct Code Formats
                                  Depending on your preference for the storage connection protocol, your completed line of code should look like one of the following variations:
                                  Using the standard HTTPS protocol (Default).
                                  -> Using the WASBS (Windows Azure Storage Blob Secure).
                                  Reference:
                                  https://stackoverflow.com/questions/75275875/create-an-azureblobdatastore-with-sdk-v2


                                  NEW QUESTION # 186
                                  You create a workspace by using Azure Machine Learning Studio.
                                  You must run a Python SDK v2 notebook in the workspace by using Azure Machine Learning Studio.
                                  You need to reset the state of the notebook.
                                  Which three actions should you use? Each correct answer presents a complete solution.
                                  NOTE: Each correct selection is worth one point.

                                  Answer: B,C,E

                                  Explanation:
                                  To reset the state of a Python SDK v2 notebook in Azure Machine Learning Studio, you can perform any of the following three individual actions:
                                  Stop the current kernel
                                  Reset the compute instance
                                  Change the current kernel
                                  Each of these steps acts as a standalone solution to clear the current runtime memory, variables, and overall execution state of your notebook.
                                  Reference:
                                  https://learn.microsoft.com/en-us/azure/machine-learning/how-to-run-jupyter-notebooks


                                  NEW QUESTION # 187
                                  ......

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