The present collection of four lecture notes is the very first contribution of this type in the field of sparse recovery. Compressed sensing is one of the important facets of the broader concept presented in the book, which by now has made connections with other branches such as mathematical imaging, inverse problems, numerical analysis and simulation. This unique collection will be of value for a broad community and may serve as a textbook for graduate courses.