•    This course addresses the basic methods used for simulating random variables and implementing Monte-Carlo and Quasi Monte-Carlo methods.
•    Simulation of stochastic processes used in neuroscience, such as Brownian motion and solutions to stochastic differential equations, will be addressed.
•    The course will introduce sampling methods in finite dimension, discretization of diffusion processes, strong and weak errors.