Pass the Microsoft Certified: Machine Learning Operations (MLOps) Engineer AI-300 Questions and answers with ExamsMirror

You create a binary classification model. You use the Fairlearn package to assess model fairness.

You must eliminate the need to retrain the model.

You need to implement the Fairlearn package.

Which algorithm should you use?

An organization operates a generative AI application in production by using Microsoft Foundry. The application serves live user traffic and is updated by a data scientist team regularly as prompts and models evolve.

The application intermittently times out during production use, which requires ongoing visibility into runtime behavior.

The team must also validate model quality and safety before releasing new updates to avoid introducing regressions.

You need to apply the correct mechanisms for continuous runtime monitoring and for release time validation.

Which mechanisms should you use for each requirement? To answer, move the appropriate mechanisms to the correct requirements. You may use each 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.

You create an Azure Machine learning workspace. The workspace contains a folder named src. The folder contains a Python script named script 1 .py.

You use the Azure Machine Learning Python SDK v2 to create a control script. You must use the control script to run script l.py as part of a training job.

You need to complete the section of script that defines the job parameters.

How should you complete the script? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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.

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?

You create a multi-class image classification deep learning model.

The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images and retrain the model.

You need to use the Azure Machine Learning Python SEX v2 to configure the schedule for the pipeline. The schedule should be defined by using the frequency and interval properties with frequency set to month ' and interval set to " 1:

Which three classes should you instantiate in sequence " ' To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

You manage an Azure Machine Learning workspace. You use Azure Machine Learning Python SDK v2 to configure a trigger to schedule a pipeline job. You need to create a time-based schedule with recurrence pattern.

Which two properties must you use to successfully configure the trigger? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

A team deploys a machine learning model to a managed online endpoint. The team monitors model performance and data quality metrics in production.

When monitoring thresholds are exceeded, the team requires an automated operational response that notifies downstream systems.

You need to configure the monitoring solution to meet the requirements.

Which configuration should you associate with each requirement as a first step? 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.

You manage an Azure Machine Learning workspace by using the Python SDK v2.

You must create a compute cluster in the workspace. The compute cluster must run workloads and properly handle interruptions. You start by calculating the maximum amount of compute resources required by the workloads and size the cluster to match the calculations.

The cluster definition includes the following properties and values:

• name= " mlcluster1’’

• size= " STANDARD.DS3.v2 "

• min_instances=1

• maxjnstances=4

• tier= " dedicated "

The cost of the compute resources must be minimized when a workload is active Of idle. Cluster property changes must not affect the maximum amount of compute resources available to the workloads run on the cluster.

You need to modify the cluster properties to minimize the cost of compute resources.

Which properties should you modify? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace that includes an AmICompute cluster and a batch endpoint. You clone a repository that contains an MLflow model to your local computer. You need to ensure that you can deploy the model to the batch endpoint.

Solution: Create a data asset in the workspace.

Does the solution meet the goal?