DP-100 Azure Machine Learning Workspace – Explore & Configure Guide is a practical learning module focused on understanding and setting up the core environment used in Microsoft Azure Machine Learning. This course is part of the DP-100 certification path and is designed for learners who want to build real-world data science solutions in the cloud. It begins by explaining the Azure Machine Learning workspace, which is the central hub where all machine learning resources, experiments, and models are managed. Learners will explore the workspace interface and understand how different components such as datasets, compute resources, and experiments are organized. The course then focuses on configuring the workspace, showing how to properly set up resources, manage access, and prepare the environment for machine learning development. This includes understanding how to structure projects for scalability and collaboration in real-world scenarios. Learners will also gain insight into how the workspace integrates with other Azure services to support end-to-end machine learning workflows. This module is ideal for data scientists, AI engineers, and learners preparing for the DP-100 certification. By the end of the course, learners will be able to confidently explore, configure, and manage an Azure Machine Learning workspace as the foundation for building advanced machine learning solutions.