This course provides a technical deep dive into unsupervised learning, focusing on identifying hidden structures in data. You will develop a strong intuition for Support Vector Machines (SVM) and master essential dimensionality reduction and grouping techniques like Principal Component Analysis (PCA) and K-Means clustering. By navigating the specialised unsupervised machine learning workflow using R, you will gain hands-on experience processing real-world datasets to uncover patterns, reduce data complexity, and perform sophisticated cluster analysis.