Azure Machine Learning for Students – Setup, Workspace & First Pipeline is a practical beginner course designed to help students start their journey in cloud-based machine learning using Microsoft Azure. The course begins with creating an Azure for Students Starter Account, guiding learners step by step on how to activate and access Azure services for free or educational use. It then moves into setting up an Azure Machine Learning workspace, which is the main environment where all machine learning projects are created and managed. Learners will understand how to configure the workspace properly to prepare for real AI development tasks. The course also covers how to create a compute instance in Azure ML, explaining how cloud computing resources are used to run machine learning models and experiments efficiently. A key part of the course is building and running the first Azure ML pipeline, where learners get hands-on experience designing a simple end-to-end workflow for data processing and model execution. This helps students understand how real machine learning systems are structured in production environments. The course is ideal for beginners and students with little or no experience in Azure or machine learning. By the end, learners will be able to set up Azure ML environments, manage compute resources, and build their first functional machine learning pipeline confidently.