Exam style questions across every AI-300 domain
Last Update 1 day ago
Total Questions : 187
Start with our free AI-300 practice questions, carefully crafted to mirror the domains, phrasing, and difficulty of the real Microsoft Certified: Machine Learning Operations (MLOps) Engineer exam. Each AI-300 exam question comes with a detailed rationale that explains not just which answer is correct but why the others fall short. That's how concepts stick. Use the free set to benchmark yourself: identify your Microsoft weak domains, see where you're losing marks, and build a focused study plan in minutes.
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 preparing training data for a fine-tuning job in Microsoft Foundry.
Real production conversations cannot be used due to compliance requirements.
You need to generate synthetic interaction data that can be used for fine-tuning a generative model.
What should you do?
You manage an Azure Machine Learning workspace named Workspace1.
You plan to create a pipeline in the Azure Machine Learning Studio designer. The pipeline must include a custom component You need to ensure the custom component can be used in the pipeline. What should you do first.
A team deploys a model to a real-time endpoint in Azure Machine Learning. You deploy some updates to the endpoint.
The endpoint returns errors after the new deployment is released.
You need to restore the service as quickly as possible.
What should you do first?
A data science team trains a classification model that predicts loan approval outcomes.
Before registering the model, the team must ensure the following:
Predictions must not disproportionately impact protected groups.
Prediction errors can be evaluated across different data segments.
You need to assess whether the model meets Responsible AI expectations.
Which two approaches should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Choose two.
A team provisions an Azure Machine Learning environment by triggering pull requests.
Deployments must be automated, auditable, and require approval before running.
You need to select a deployment automation tool.
Which tool should you use?
You need to standardize how Fabrikam Inc. manages machine learning assets.
Which action should you perform first?
You need to isolate training workloads while remaining cost-aware to address Fabrikam Inc.’s issues, constraints, and technical requirements.
What should you implement?
You have an Azure Machine Learning workspace. You are running an experiment on your local computer.
You need to ensure that you can use MLflow Tracking with Azure Machine Learning Python SDK v2 to store metrics and artifacts from your local experiment runs in the workspace.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
You manage an Azure Machine Learning workspace. You design a training job that is configured with a serverless compute. The serverless compute must have a specific instance type and count
You need to configure the serverless compute by using Azure Machine Learning Python SDK v2. What should you do?
