Formal instructional programs that teach machine learning collect principles, methods, and practical exercises into sequenced modules. These programs typically introduce fundamental concepts such as supervised and unsupervised learning, model evaluation metrics, and data preparation. They may also present workflow topics like experimental design, reproducibility, and basic deployment ideas. The aim of such a course structure is to give learners a scaffolded way to develop both conceptual underst