This course 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.
1. Conditional probability. Random vectors.
2. Simulation algorithms.
3. Random processes. Poisson processes.
4. Markov chains and processes.
Applied Probability 1 (1st year).
Statistical Principles and Methods (2nd year).
Give kind of exam for session 1 and session 2: written, allowed documents or not, oral, practical work, reports, plan, vivas
N1 = (TP + 2 * E1) / 3
N2 = (TP + 2 * E2) / 3
The course exists in the following branches:
Course ID : 4MM1PPI
The course is attached to the following structures:
You can find this course among all other courses.
Date of update January 15, 2017