IV111 Probability in Computer Science

Faculty of Informatics
Spring 2007
Extent and Intensity
2/2. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Jan Bouda, Ph.D. (lecturer)
doc. RNDr. Tomáš Brázdil, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Contact Person: prof. RNDr. Antonín Kučera, Ph.D.
Timetable
Wed 8:00–9:50 A107
  • Timetable of Seminar Groups:
IV111/01: Wed 12:00–13:50 B411, J. Bouda
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 18 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. Aplications in computer science (hash functions, random generation, 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
The course is taught annually.
The course is also listed under the following terms Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Spring 2007, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2007/IV111