Stochastic models for collective motions of populations In this thesis stochastic dynamics modelling collective motions of populations one of the most mysterious type of biological phenomena are considered. For a system of N particle like individuals two kinds of asymptotic behaviours are studied : ergodicity and flocking properties in long time and propagation of chaos when the number N of agents goes to infinity. Cucker and Smale deterministic mean field kinetic model for a population without a hierarchical structure is the starting point of our journey : the first two chapters are dedicated to the understanding of various stochastic dynamics it inspires with random noise added in different ways. The third chapter an attempt to improve those results is built upon the cluster expansion method a technique from statistical mechanics. Exponential ergodicity is obtained for a class of non Markovian process with non regular drift. In the final part the focus shifts onto a stochastic system of interacting particles derived from Keller and Segel 2 D parabolicelliptic model for ...