Stochastic processes are the fundamental objects for time dependent phenomena that involve randomness. Applications range from physics, biology, and chemistry over information theory, machine learning, to finance.
We study stochastic processes both in discrete and continuous time. The content of the course includes conditional expectations, Markov chains and processes, martingals, recurrence and transience, Poisson processes, random walks, Brownian motion.
There will be a course Stochastic Analysis in summmer 2026 where we develop the theory of stochastic integration and stochastic differential equations.