This short course teaches you how to train, validate, and improve predictive models using practical, industry-ready workflows. You’ll learn to apply supervised and unsupervised algorithms, run 5-fold cross-validation, and interpret metrics like precision, recall, and F1 to understand model reliability. Through videos, guided reflections, readings, and hands-on labs, you’ll practice building complete pipelines, engineering new features, and evaluating model improvements against performance targets. By the end of the course, you’ll be able to apply validation techniques confidently, iterate on your models using data-driven decisions, and explain performance results clearly to technical and non-technical stakeholders.