Machine Learning Foundations
A jargon-free introduction to what machine learning is, its three main types, and the data-to-model workflow behind every ML project.
Supervised Learning Essentials
A practical tour of regression, classification, and the evaluation metrics — accuracy, precision, recall, and overfitting checks — that reveal whether a model truly works.
Practical ML: From Idea to Model
Turn a fuzzy business goal into a concrete ML task, prepare honest data, beat a baseline, and ship a model you can monitor and trust.