This course focuses on techniques of learning from data, on detecting hidden structure and regularity patterns associated with the generation mechanisms of the data. This discovered  information is instrumental not only in the analysis and understanding of the nature of the data, but also to build predictors, classifiers, regressors, and to develop efficient algorithms. The course recapitulates the basics of the least squares techniques, the classical classification and regression algorithms.  It then proceeds to discuss the role of convexity, to develop kernel-based algorithms, sparsity-promoting approaches in parameter learning