Microsoft AI-300 Exam Questions

A company's platform engineers manage the resource settings and governance of Microsoft Foundry.

Developers must be able to create and update project assets but must not be able to change resource-level configurations.

You need to enforce least privilege access for the engineers and developers.

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 have a Microsoft Foundry project.

You plan to use the Microsoft Foundry portal to fine-tune a base Azure OpenAI Service model that can accept both text and images as input.

You need to choose the suitable model.

Which model should you choose?

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 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?

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?