FI:IV111 Probability in CS - Course Information

IV111 Probability in Computer Science

Faculty of Informatics
Spring 2008

Extent and Intensity

2/2. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).

Teacher(s)

Guaranteed by

Timetable

Thu 8:00–9:50 A107

IV111/01: Thu 10:00–11:50 B007, J. Bouda
IV111/02: Tue 10:00–11:50 B007, V. Forejt

Prerequisites

Knowledge of basic discrete structures (say as taught in IB000).

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

there are 37 fields of study the course is directly associated with, display

Course objectives

This subject gives introductory knowledge of probability theory, with an emphasis on discrete probability and its applications in computing.

Syllabus

Probability. Discrete probabilistic space. Random variable and its use. Expectation and variation. Chebyshev inequality. Kolmogorov inequality. Weak and strong law of large numbers. Random processes. Markov processes. Entropy. Information. Aplications in computer science (information theory, coding theory, cryptography, randomized algorithms, etc).

Literature

FELLER, William. An introduction to probability theory and its applications. 3rd ed. [New York]: John Wiley & Sons, 1968, xviii, 509. ISBN 9780471257080. info

Language of instruction

Czech

Further Comments

Study Materials
The course is taught annually.