Model Training Optimization with Azure Machine Learning

Training machine learning models efficiently requires moving beyond manual, local experimentation to structured cloud workflows. This text-based course guides you through organizing, executing, and optimizing your training workloads within Azure Machine Learning, helping you transition from basic scripts to fully automated pipelines. What you'll learn: Understand foundational Azure Machine Learning concepts, including workspaces, compute instances, and environments; Configure and run training scripts as managed cloud jobs; Create reusable components to modularize your machine learning workflows; Build and orchestrate robust end-to-end training pipelines; Track and monitor model metrics to continuously analyze and improve training performance. The course begins with essential terminology and setup before walking you through the practical steps of job configuration, pipeline creation, and performance tuning. Perfect for aspiring data scientists and developers new to cloud ML, this course assumes basic Python familiarity but requires no prior Azure experience. Begin optimizing your machine learning workflows today.