FI:IV111 Probability in CS - Course Information

IV111 Probability in Computer Science

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)
RNDr. Vojtěch Forejt, Ph.D., LL.B. (Hons) (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

Thu 8:00–9:50 A107

• Timetable of Seminar Groups:

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

• Applied Informatics (programme FI, B-AP)
• Applied Informatics (programme FI, N-AP)
• Information Technology Security (programme FI, N-IN)
• Bioinformatics (programme FI, B-AP)
• Bioinformatics (programme FI, N-AP)
• Information Systems (programme FI, N-IN)
• Informatics with another discipline (programme FI, B-BI)
• Informatics with another discipline (programme FI, B-FY)
• Informatics with another discipline (programme FI, B-GE)
• Informatics with another discipline (programme FI, B-GK)
• Informatics with another discipline (programme FI, B-CH)
• Informatics with another discipline (programme FI, B-IO)
• Informatics with another discipline (programme FI, B-MA)
• Informatics with another discipline (programme FI, B-SO)
• Informatics with another discipline (programme FI, B-TV)
• Informatics (programme FI, B-IN)
• Informatics (programme FI, M-IN)
• Informatics (programme FI, N-IN)
• Mathematical Informatics (programme FI, B-IN)
• Parallel and Distributed Systems (programme FI, B-IN)
• Parallel and Distributed Systems (programme FI, N-IN)
• Computer Graphics and Image Processing (programme FI, B-IN)
• Computer Graphics (programme FI, N-IN)
• Computer Networks and Communication (programme FI, B-IN)
• Computer Networks and Communication (programme FI, N-IN)
• Computer Systems and Data Processing (programme FI, B-IN)
• Computer Systems (programme FI, N-IN)
• Embedded Systems (eng.) (programme FI, N-IN)
• Programmable Technical Structures (programme FI, B-IN)
• Theoretical Informatics (programme FI, N-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-TV)
• Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
• Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
• Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
• Image Processing (programme FI, N-AP)

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.

• Enrolment Statistics (Spring 2008, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring2008/IV111