This project explores fundamental techniques of machine learning learnt from an exercise, focusing on both supervised and unsupervised learning methods. It includes a Jupyter Notebook that demonstrates various algorithms applied to a dataset provided in inpFle_BCCP.csv. The dataset is a bank dataset that stores information on their customers such as gender, age and estimated salary. With the dataset some techniques such as K-means and Decision Trees will be utilised to get a better understanding of the data.