Machine Learning and Applied AI use data-driven algorithms to model and predict outcomes, and are applied to solve complex problems and enhance real-world decision-making.
Intermediate
Fundamentals of Regression in Machine Learning
Explore regression techniques in supervised machine learning, from simple and multiple linear models to regularisation and Bayesian approaches for predictive analysis.
Clustering and Unsupervised Methods in Machine Learning
Discover unsupervised machine learning methods, including k-means, hierarchical, and density-based clustering, along with dimensionality reduction techniques.
