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The course is in two parts.
Part 1. Probability:
This part is an introduction with examples to probability models and methods useful in computer science. It gives theoretical material in probability and statistics and presents applications in the modelling and assessment of computer systems.
Part 2. Communication Networks
1. Conditional probability. Random vectors.
2. Simulation algorithms.
3. Random processes. Poisson processes.
4. Markov chains and processes.
5. Models and evaluation of communication networks.
6. Simulation of discrete events.
7. Trafic models.
8. Service quality and loss.
9. Robustness of the M/M/1 model
Applied Probability and Statistical Principles and Methods (1rst year Ensimag).
S.M. ROSS : Probability Models for Computer Science, Academic Press, 2001.
K.S. TRIVEDI : Probability and Statistics with Reliability, Queuing and Computer Science Applications, Wiley,
1st session : Written exam 1.5h on Part 1+ written exam 1.5h on Part 2+ continous assessment
2nd session : Written exam 2h