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Microsoft AI-300 Practice Q&A's

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Microsoft AI-300 Exam Syllabus Topics:

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

                                  Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

                                  Question #1

                                  You are preparing to build a deep learning convolutional neural network model for image classification. You create a script to train the model using CUDA devices.
                                  You must submit an experiment that runs this script in the Azure Machine Learning workspace.
                                  The following compute resources are available:
                                  a Microsoft Surface device on which Microsoft Office has been installed. Corporate IT policies prevent the installation of additional software a Compute Instance named ds-workstation in the workspace with 2 CPUs and 8 GB of memory an Azure Machine Learning compute target named cpu-cluster with eight CPU-based nodes an Azure Machine Learning compute target named gpu-cluster with four CPU and GPU-based nodes You need to specify the compute resources to be used for running the code to submit the experiment, and for running the script in order to minimize model training time.
                                  Which resources should the data scientist use? To answer, select the appropriate options in the answer area.
                                  NOTE: Each correct selection is worth one point.

                                  Reveal Solution  Discussion  0

                                  Correct Answer:


                                  Explanation:

                                  Question #2

                                  You have an Azure Machine Learning workspace named workspaces.
                                  You must add a datastore that connects an Azure Blob storage container to workspaces. You must be able to configure a privilege level.
                                  You need to configure authentication.
                                  Which authentication method should you use?

                                  • A. Account key
                                  • B. SAS token
                                  • C. Managed identity
                                  • D. Service principal
                                  Reveal Solution  Discussion  0

                                  Correct Answer: C  🗳️

                                  Question #3

                                  You have an Azure subscription that contains a resource group named rg-ml.
                                  You plan to create an Azure Machine Learning workspace named workspacel in rg-ml by using Azure Machine Learning Python SDK v2.
                                  You need to ensure workspacel is configured to prevent the collection of potentially sensitive data by Microsoft diagnostics.
                                  How should you complete the provided code? To answer, select the appropnate options in the answer area.
                                  NOTE: Each correct selection is worth one point.

                                  Reveal Solution  Discussion  0

                                  Correct Answer:


                                  Explanation:

                                  Question #4

                                  A company is standardizing generative AI development across multiple teams.
                                  Each team requires an isolated workspace. Governance and shared connections must be centrally managed.
                                  You need to implement a Microsoft Foundry environment structure that supports centralized governance and team isolation.
                                  Which type of configuration should you use for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration 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.

                                  Reveal Solution  Discussion  0

                                  Correct Answer:


                                  Explanation:
                                  An Azure AI Hub is the top-level governance container in Microsoft Foundry: it holds shared connections to Azure OpenAI, Azure AI Search, Azure Storage, and other services; it defines network isolation policies; it manages billing and quota at the organizational level. Multiple teams share these resources without each team needing to configure their own connections or negotiate quota independently. An Azure AI Project sits inside the Hub and provides team-level isolation: each project has its own experiments, deployments, prompt flows, evaluations, and fine-tuning jobs, all governed by the Hub ' s shared infrastructure. Different teams get their own project with independent access controls via RBAC, while the platform team manages the shared Hub.
                                  This pattern eliminates redundant resource configurations across teams while maintaining clear team-level boundaries - the correct structure for centralized governance with team isolation.
                                  Microsoft Learn Reference Topic: Microsoft Azure AI Foundry hub and project architecture - Centralized governance and team isolation

                                  Question #5

                                  You are designing a new machine learning solution to predict customer churn by using Azure Machine Learning. You have raw data in CSV format stored in Azure Data Lake.
                                  You need to design the solution so that it can efficiently handle large-scale model training and iterative development.
                                  Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
                                  NOTE: Each correct selection is worth one point

                                  • A. Schedule training using an Azure Data Factory pipeline.
                                  • B. Register the data as a tabular dataset in the Azure Machine Learning workspace.
                                  • C. Convert the data into the JSONL format and upload into Blob Storage.
                                  • D. Configure an Azure Machine Learning compute cluster for model training.
                                  • E. Configure an Azure Machine Learning compute instance for model training.
                                  Reveal Solution  Discussion  0

                                  Correct Answer: B,D  🗳️

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