AI-300 Exam Questions & Answers

You plan to filter your traces to identify issues while observing how the application is responding. The solution must not use an external knowledge base.

You need to select an evaluation metric.

Which built-in evaluator should you use?

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?

A data science team completes multiple training runs within an experiment by using MLflow.

The team wants to store a selected model in Azure Machine Learning so that it can be versioned and deployed later.

The model must be versioned centrally for reuse across environments.

You need to version the trained model.

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

A team is working in Microsoft Foundry to test and compare large language model (LLM) prompt variants in a development environment.

The team requires consistent inputs to evaluate prompt variants without relying on live user traffic.

You need to create a controlled evaluation of input data.

Which action should you perform first?

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: Create prompt variants and compare their outputs in the Evaluation experience.

Does the solution meet the goal?