Pass the Microsoft Certified: Machine Learning Operations (MLOps) Engineer AI-300 Questions and answers with Dumpstech

You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2. You create a General Purpose v2 Azure storage account named mlstorage1. The storage account includes a publicly accessible container named mlcontainer1. The container stores 10 blobs with files in the CSV format.

You must develop Python SDK v2 code to create a data asset referencing all blobs in the container named mlcontainer1.

You need to complete the Python SDK v2 code.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace.

You plan to run a job to tram a model as an MLflow model output.

You need to specify the output mode of the MLflow model.

Which three modes can you specify? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

You are designing a new machine learning solution to predict customer churn by using Azure Machine Learning. You have raw data in CSV format stored in Azure Data Lake.

You need to design the solution so that it can efficiently handle large-scale model training and iterative development.

Which two actions should you perform? Each correct answer presents part of the solution. Choose two.

NOTE: Each correct selection is worth one point

You manage an Azure Machine Learning workspace. You train a model named model1.

You must identify the features to modify for a differing model prediction result.

You need to configure the Responsible Al (RAI) dashboard for model1.

Which three actions should you perform in sequence? To answer move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

You are designing an Azure Machine Learning solution for traffic optimization.

The model must be deployed as a web service on a serverless compute and provide real-time predictions based on current traffic and weather conditions. You need to choose an inferencing strategy for the solution. Which compute should you use?

A team is building a generative AI agent by using Retrieval-Augmented Generation (RAG) in Microsoft Foundry.

The team frequently updates prompt content. The team must be able to track changes across contributors while avoiding full application redeployments.

You need to enable rapid prompt iteration with traceability. Applications consuming the agent must be able to use updated prompts without requiring redeployment.

What should you configure for each requirement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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 script.py --trainingdata ${{inputs.training_data}}

Does the solution meet the goal?

You create an MLflow model

You must deploy the model to Azure Machine Learning for batch inference.

You need to create the batch deployment.

Which two components should you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point

You manage an Azure Machine Learning workspace.

You schedule a pipeline job by using Azure Machine Learning Python SDK v2.

You need to decide whether the time-based schedule with cron expression is implemented correctly.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace named workspaces.

You must add a datastore that connects an Azure Blob storage container to workspaces. You must be able to configure a privilege level.

You need to configure authentication.

Which authentication method should you use?