This course introduces the fundamentals of unsupervised learning, focusing on discovering hidden patterns within data. You will develop an understanding of Support Vector Machines (SVM) and master essential dimensionality reduction and grouping techniques, such as Principal Component Analysis (PCA) and K-Means clustering. By navigating the complete machine learning modelling workflow, from data preprocessing to model evaluation, using Python and scikit-learn, you will gain hands-on experience applying these powerful algorithms to real-world datasets.