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Microsoft AI-300 Exam Syllabus Topics:

Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

1. You need to run large-scale inference jobs on millions of records periodically. Jobs are not latency-sensitive but must be cost-efficient and scalable. Which deployment option is MOST appropriate?

A) Local endpoint
B) Managed online endpoint
C) Batch endpoint
D) Notebook execution

2. 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.

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.

4. You manage an Azure Machine Learning workspace. You have an environment for training jobs which uses an existing Docker image.
A new version of the Docker image is available.
You need to use the latest version of the Docker image for the environment configuration by using the Azure Machine Learning SDK v2.
What should you do?

A) Modify the conda_file to specify the new version of the Docker image.
B) Use the Environment class to create a new version of the environment.
C) Use the create_or_update method to change the tag of the image.
D) Change the description parameter of the environment configuration.

5. You deploy a model to production but do not have labeled data available for evaluating prediction accuracy. However, you must monitor model health continuously. What is the BEST strategy?

A) Disable monitoring
B) Monitor accuracy metrics
C) Use data drift detection
D) Perform manual evaluation only

Solutions: