Microsoft Operationalizing Machine Learning and Generative AI Solutions AI-300 Exam Questions

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?

A team manages an Azure Machine Learning workspace and deploys a model to an endpoint.

A deployed online endpoint shows inconsistent response times during periods of high traffic.

You need to identify potential performance degradation.

Which three metrics should you monitor? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Choose three

An organization is deploying several generative AI workloads by using Microsoft Foundry. Each workload must meet different requirements related to data governance, task specialization, and operational cost control.

The organization requires models that meet the following requirements:

Model behavior aligns with the task being performed.

Data handling aligns with internal governance policies.

Operational complexity and cost are justified by workload needs.

You need to select the foundation model options that meet the requirements.

Which three models can you select? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point. Choose three.

A financial services company is deploying Microsoft Foundry to host generative AI workloads that process regulated customer data. The Microsoft Foundry environment must prevent any public network exposure while still allowing services managed by Microsoft Foundry to communicate with dependent Azure resources.

Security auditors require that all traffic to and from the Microsoft Foundry resource remain on private networks, with no public endpoints available.

You need to configure the Microsoft Foundry environment so that network access is restricted while maintaining full platform functionality.

Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Choose two.

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?

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 on the review screen.

You manage an Azure Machine Learning workspace. The Python script named script.py reads an argument named training_data.

The training_data argument specifies the path to the training data in a file named dataset1.csv.

You plan to run the script.py Python script as a command job that trains a machine learning model.

You need to provide the command to pass the path for the dataset as a parameter value when you submit the script as a training job.

Solution: python train.py --training_data training_data

Does the solution meet the goal?

prompt variants to improve the user experience.

When comparing prompt variants, the team plans to assess whether the generated responses are grammatically correct.

You need to evaluate the quality of the language from the generated responses.

Which evaluator should you use?