The School aims to introduce students to the mathematical and statistical underpinnings of some of the latest Data Science methods that seek to address the challenge of Big Data analysis. There will be an emphasis on matricial methods both in modelling and in numerical computations. The topics covered will include Randomized Numerical Linear Algebra, Deep Generative Models, Bayesian Nonparametric Models and their Asymptotic Properties, Modern Graphical Models and High- Dimensional Statistics Based on Random Matrix Theory.