Microsoft AI-300 Exam Dumps

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.

Show Answer Hide Answer

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?

Show Answer Hide Answer

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 work in Microsoft Foundry with a prompt flow.

You must manually evaluate prompts and compare results across prompt variants.

You need to capture the inputs, outputs, token usage, and latencies for each flow run for the evaluation.

Solution: Use the prompt flow SDK to enable tracing for the flow before executing runs. Then run the flow to generate traceable results.

Does the solution meet the goal?

Show Answer Hide Answer

A team is experimenting with traditional models for a classification workflow in Azure Machine Learning.

The team requires a consistent way to manage assets that are created during experimentation.

You need to ensure that artifacts can be reused and governed across projects.

Which asset should you register?

Show Answer Hide Answer

A team is deploying machine learning models to a production inference endpoint in Azure Machine Learning.

The team requires a safe way to validate a new model version without disrupting existing users.

You need to recommend a deployment strategy for controlled testing of a new model version.

What should you configure?

Show Answer Hide Answer