This course developed by Universitat Politècnica de Catalunya and Barcelona Supercomputing Center provides an applied approach to Deep Learning. It chooses to present an overview of methods and approaches, instead of going in full detail of any particular aspect. The course has three types of sessions: Theory (most content provided by lecturer often through slides), Guided Laboratory (content provided by lecturer to be used by students) and Autonomous Laboratory (work by students with support from lecturer available). Most of the course (CNNs, RNNs, Transfer Learning and Transformers) is taught by Dario Garcia-Gasulla. The High Performance Computing (HPC) part is taught by Marc Casas. Lecturers Dario Garcia-Gasulla (Course coordinator, BSC, [email protected]) Marc Casas (BSC, [email protected])