1. Introduction to Stochastic Processes
2. Discrete Markov Chains
3. Continuous time Markov Chains
4. Renewal Processes
5. Queuing theory
6. Random Graphs
7. Case studies:
Monte Carlo Algorithm, PageRank Algorithm, Call centers, Social networks.
Learning activities and methodology
Theory (4 ECTS). Theory classes with additional material available on the Web.
Practical classes (2 ECTS) Problem solving classes. Problem based learning classes.
% end-of-term-examination 60
% of continuous assessment (assigments, laboratory, practicals...) 40
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN
The course syllabus may change due academic events or other reasons.