RegMLis a 22-hour advanced machine learning course that includes theoretically oriented classes and practical laboratory sessions, essentially being a compressed version of the Statistical Learning Theory and Applications course taught at MIT. The course covers fundamental aspects as well as recent advances in Machine Learning with special emphasis on high dimensional data and core set techniques, the latter being regularization methods.
In addition to the 22-hour course, students had the opportunity to be updated on research by renowned experts from UK, Germany, and Italy. More information and material can be found on the course webpage.