This Azure Machine Learning Studio basics course is designed for beginners who want to understand how to work with Microsoft Azure’s machine learning environment. The course provides a simple and structured introduction to the core components of Azure ML Studio and how they are used to build and manage machine learning projects.
Students will begin by learning what Azure Machine Learning Studio is and how it supports end-to-end machine learning workflows in the cloud. The course then guides learners through provisioning a workspace, which is the foundation for organizing and managing machine learning assets.
A key focus of the course is working with datasets and experiments, helping learners understand how data is imported, managed, and used to train models. The course also introduces Jupyter Notebooks inside Azure ML Studio, allowing learners to write and run Python code in a cloud environment.
In addition, students will learn how to manage project assets, understand different types of data sources, and explore big data workflows within Azure. The course also provides an overview of tools like the Cortana Intelligence Gallery and how they fit into the Azure ML ecosystem.
By the end of the course, learners will have a clear understanding of Azure Machine Learning Studio fundamentals and how to organize, run, and manage basic machine learning projects in the cloud.
