This Azure Machine Learning Designer course is designed for beginners who want to build machine learning models without heavy coding using Microsoft Azure’s visual interface. The course focuses on guiding learners through the complete machine learning workflow using Azure ML Designer.
Students will begin by creating an Azure student account and setting up their machine learning workspace. The course then introduces compute instances, explaining how to configure the environment needed to run experiments and build models in the cloud.
A key focus of the course is data preparation and transformation using Azure ML Designer tools. Learners will explore how to summarize data, normalize datasets, and prepare data for machine learning experiments using visual pipelines.
The course also covers experiments and jobs inside Azure ML, helping students understand how to track and manage machine learning workflows. Learners will then move into modeling, where they build machine learning models using a drag-and-drop interface without writing code.
In addition, the course introduces model interpretation and explainability features, allowing learners to understand how predictions are generated and how models make decisions.
By the end of the course, learners will be able to confidently use Azure Machine Learning Designer to create, train, evaluate, and interpret machine learning models using a fully visual, no-code approach.
