Azure Machine Learning Studio – Data Preparation, Modeling & Deployment Course is a practical beginner-friendly program focused on building end-to-end machine learning workflows using Microsoft Azure. The course starts with an introduction to Azure Machine Learning Studio and explains how to upload and manage datasets within the platform. Learners will understand how to prepare raw data for analysis, which is a critical step in any machine learning project. The course then moves into data preprocessing techniques, including summarizing datasets, normalizing values, and handling missing data to ensure high-quality inputs for model training. After preparing the data, learners are introduced to the concept of prediction in machine learning, where they explore how models generate outputs based on learned patterns. This section helps build a strong understanding of how predictive systems work in real-world applications. Finally, the course demonstrates how to publish machine learning models to the Azure Gallery, allowing users to share and deploy their solutions effectively. This complete workflow—from data preparation to deployment—gives learners hands-on experience in building real AI solutions. The course is ideal for beginners, students, and professionals who want to learn practical machine learning using Azure tools. By the end, learners will be able to confidently manage data, build models, and deploy machine learning solutions in Azure Machine Learning Studio.
