Foundations of AI & Machine Learning

This beginner-friendly course introduces the core ideas behind AI and machine learning. You will learn what AI and ML are, how data is prepared for modelling, and how supervised learning (regression, classification, decision trees, random forests) and unsupervised learning (clustering, dimensionality reduction) work. The course also covers model evaluation, cross-validation, overfitting, feature engineering, and an introduction to neural networks. It ends with responsible AI, covering bias, fairness, and ethics. Basic Python is helpful; high-school-level maths is enough.