Microsoft AI-300 Exam Dumps

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.

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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?

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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?

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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?

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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?

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You need to isolate training workloads while remaining cost-aware to address Fabrikam Inc.'s issues, constraints, and technical requirements.

What should you implement?

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