Title. Asymptotic Geometric Analysis Brief description. The course will be an introduction to Convex Geometry in high dimensions, local theory of Banach spaces and modern trends in high dimension probability. The course is organized as follows: -- Brunn-Minkowski inequality, functional forms and applications. Symmetrization and related inequalities. The concentration of measure phenomenon. Poincare and log-Sobolev inequalities. Semi-group techniques and the Brascamp-Lieb family of inequalities. --Convex bodies and their ``Positions". Dvoretzky-Rogers factorization and Dvoretzky's theorem. Kashin's theorem and applications to RIP matrices. -- Type cotype and Lp spaces. K-convex spacesa nd Pisier's theorem. Entropy numbers, M-positions of convex bodies and the Bourgain-Milman theorem. The quotient of subspace theorem.