Data mining studies algorithms and computational paradigms that allow computers to find patterns and regularities in dataset, perform predictions and generally improve the performance through interaction with data. It is currently regarded as the key element of a more general knowledge discovery process that deals with extracting useful knowledge from raw data. This course will offer students advanced algorithms for mining various types of complex data, especially imaging data.  The curriculum will start with the classical data mining methods for tabular and graph data and next move into data-driven imaging data mining with advanced algorithms. We will review different model architectures and learning algorithms such as clustering, classification and graph neural networks. We will go into a few research topics including self-supervised machine learning and various real-world applications.