The course is structured into two main parts. The first is the basic knowledge of parallel and distributed algorithm analysis. The second is distributed algorithms for some specific problems, including convex optimization; matrix factorization; machine learning; neural networks; numerical linear algebra; large graph analysis; data stream algorithms.