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Featuring 40 multiple-choice questions with unlimited attempts, this practice exam focuses on executing and managing training workflows in Azure. You’ll learn to run training command jobs in Azure Machine Learning and track experiments using MLflow jobs, gaining practical experience in orchestrating, logging, and monitoring model training processes. This practice exam is part of the preparation series for DP-100: Designing and Implementing a Data Science Solution on Azure.

Featuring 40 multiple-choice questions with unlimited attempts, this practice exam helps you master hyperparameter tuning and pipeline execution in Azure Machine Learning. You’ll learn to optimize model performance using Azure's hyperparameter tuning capabilities and build end-to-end workflows by running pipelines efficiently. This practice exam is part of the preparation series for DP-100: Designing and Implementing a Data Science Solution on Azure.

Featuring 40 multiple-choice questions with unlimited attempts, this practice exam focuses on operationalizing and evaluating models in Azure. You'll learn how to register MLflow models in Azure Machine Learning for versioning and deployment, and how to build Responsible AI dashboards to assess fairness, explainability, and error analysis. This practice exam is part of the preparation series for DP-100: Designing and Implementing a Data Science Solution on Azure.

Featuring 40 multiple-choice questions with unlimited attempts, this practice exam guides you through the process of planning AI application development on Azure and effectively using the Azure AI Foundry portal. You'll learn to design scalable AI solutions and choose and deploy models from the built-in catalog, aligning cloud-based tools with your application goals. This practice exam is part of the preparation series for DP-100: Designing and Implementing a Data Science Solution on Azure.

Featuring 40 multiple-choice questions with unlimited attempts, this practice exam focuses on advanced generative AI development in Azure AI Foundry. You’ll learn to build Retrieval-Augmented Generation (RAG) applications using custom data and perform language model finetuning to tailor model behavior for domain-specific tasks. This practice exam is part of the preparation series for DP-100: Designing and Implementing a Data Science Solution on Azure.

Featuring 40 multiple-choice questions with unlimited attempts, this practice exam focuses on developing and evaluating responsible generative AI using Azure AI Foundry. You’ll learn how to build ethical, transparent, and fair generative AI applications, and evaluate models directly within the Azure AI Foundry portal using built-in tools for safety, quality, and performance assessments. This practice exam is part of the preparation series for DP-100: Designing and Implementing a Data Science Solution on Azure.