The course consists of 7 lectures (2 hours each) and 7 Lab sessions (4 hours each) related to the lectures. Grades are based on the performance during the Labs (50 % of the final grade) and the accomplishment of an individual (final) project  (50 % of the final grade). 

Lecture 1: Introduction to computer modeling. Basic notions from the theory of probability and statistical physics. Time and ensemble averages. Computing of statistical integrals by Monte Carlo.
Lab1: Computing of definitive integrals by Monte Carlo. Random number generators. (in Fortan, PASCAL or Basic)
Lecture 2: Modeling of microcanonical, canonical and grand canonical ensembles. Algorithms, strategies, initial & boundary conditions. Accuracy of the Monte Carlo estimates.
Lab 2: Phase transitions in a two-dimensional Ising model. (in Fortan, PASCAL or Basic)
Lecture 3: Monte Carlo simulation of magnetic phase diagrams, spin glasses, order/disorder phenomena in alloys and proteins, crystal growth. 
Lab 3: Growth of a two-dimensional crystal described by the model of Kosell. (in Fortan, PASCAL or Basic)
Lecture 4: Modeling of classical & quantum liquids and soft solids (polymers). 
Lab 4: Vapour-liquid-solid phase transitions in a two-dimensional hard-disk-like liquid. Boltzmann distribution by the algorithm of von Neumann. (in Fortan, PASCAL or Basic)
Lecture 5: Kinetic processes by Monte Carlo. 
Lab 5: Self-diffusion on a two-dimensional square lattice. (in Fortan, PASCAL or Basic)
Lecture 6: Scattering, implantation, sputtering, radiation damages modeled by Monte Carlo. Principles of reverse Monte Carlo.
Lab 6: Optimization of the characteristics of a photomultiplyer (dynode) by Monte Carlo simulations. (in Fortan, PASCAL or Basic)
Lecture 7. Geometrical phase transitions and percolation phenomena by Monte Carlo. Image reconstruction by Monte Carlo.
Lab 7: Simulation of percolation clusters with fractal dimensions. (in Fortan, PASCAL or Basic) 
8. Individual project. (end semester)