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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.

Human-made tutorials, enhanced with AI, edited for quality and powered by chat support and quizzes. Behind every data-driven decision lies a query crafted by someone who knows how to ask the right questions.

Crafted by humans, supported by AI and rigorously edited to ensure quality. Data can be overwhelming—but with Python, you can turn complexity into clarity.

Human-made tutorials enhanced with AI and polished to a high standard you can trust. Writing R code is one thing—writing efficient, reusable R code is another.

Every tutorial begins with human authors, gains from AI, and is polished by human editors — complete with chat tools and interactive quizzes to keep learning active. Developers today have access to AI tools that can be integrated into applications with minimal friction.