As a starting point, we will recall basics of probability and statistics, with an emphasis on numerical techniques (probability functions generation, data analysis). Data analysis will give the chance to introduce modeling in the simple form of data fitting. A large fraction of the course will be devoted to applications of Markov processes theory. Modeling of queues will be introduced; simple examples of dynamic MonteCarlo will also be tackled. An elementary introduction to stochastic differential equations will be provided, in particular facing Langevin equation (brownian motion and tree-cutting problem). Basics of percolation theory will be introduced as an example of how a simple model can model a variety of phenomena.