• 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 and mathematical finance, 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. Exercices will be done on paper and on the computer (using Python language)