AI-300 Exam Question 1

An Azure Machine Learning workspace processes sensitive training data.
The workspace must NOT be accessible from the public internet.
You need to restrict network access.
Which configuration should you implement?
  • AI-300 Exam Question 2

    A company's platform engineers manage the resource settings and governance of Microsoft Foundry.
    Developers must be able to create and update project assets but must not be able to change resource-level configurations.
    You need to enforce least privilege access for the engineers and developers.
    Which two actions should you perform? Each correct answer presents part of the solution.
    Choose two.
    NOTE: Each correct selection is worth one point.
  • AI-300 Exam Question 3

    Drag and Drop Question
    A team manages prompts that are used by a generative AI application built on Microsoft Foundry.
    Multiple developers contribute prompt updates, and changes must be reviewed and tracked over time.
    The team requires that:
    - Prompt changes are reviewed before being applied to the version in
    production.
    - Previous prompt versions can be restored if issues occur.
    - Prompt updates follow the same governance practices as the
    application code.
    You need to implement a controlled process for managing and updating prompts in production.
    How should you manage prompt updates to meet the requirements? To answer, move the appropriate actions to the correct requirements. 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.

    AI-300 Exam Question 4

    You manage an Azure Machine learning workspace. You develop a machine learning model.
    You must deploy the model to use a low-priority VM with a pricing discount.
    You need to deploy the model.
    Which compute target should you use?
  • AI-300 Exam Question 5

    Drag and Drop Question
    An organization uses Microsoft Foundry to develop generative AI projects that access shared Azure resources such as storage accounts and vector databases.
    The organization s security policy requires eliminating secret key-based authentication and enforcing least-privilege access.
    You must configure identity and access so that:
    Services authenticate without stored credentials.
    Permissions are scoped appropriately across projects and shared resources.
    You need to configure the appropriate identity or access mechanism for each requirement.
    What should you configure in Microsoft Foundry to meet each requirement? To answer, move the appropriate configuration mechanisms to the correct requirements. You may use each configuration mechanism 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.