IV124 Complex Networks

Faculty of Informatics
Spring 2025
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
RNDr. Josef Spurný, Ph.D. (lecturer)
Ing. Eva Výtvarová (lecturer)
RNDr. Jan Fousek, Ph.D. (lecturer)
doc. RNDr. Eva Hladká, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Eva Hladká, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics
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
Course objectives
Many complex systems can be viewed as a network of interacting units. This view helps to study and understand important phenomena present in systems such as human brain, internet, economy, social groups and others. The prezence of big data stimulated development of fundamental theories to describe and analyse complex networks in many fields.
Learning outcomes
The students will be able to describe the local and global network properties. They will understand the principles of generating natural or man-made complex networks. The students will be able to apply the complex network analysis to empirical data sets across the application domains in both humanities and sciences. Given raw data, they will be also capable of designing a network-oriented analysis, formulate relevant hypothesis and interpret correctly the results.
Syllabus
  • Intro
  • Random graphs
  • Central nodes
  • COmunity structure
  • Application of centrality and modularity
  • Power law I
  • power-law II
  • Small-world networks
  • Random walks
  • Robustness and stability
  • Social-economic networks
  • Internet as a complex network
  • Biologic networks
  • Visualisation
Literature
    recommended literature
  • BARABÁSI, Albert-László and Márton PÓSFAI. Network science. First published. Cambridge: Cambridge University Press, 2016, xviii, 456. ISBN 9781107076266. info
  • NEWMAN, M. E. J. Networks : an introduction. Oxford: Oxford University Press, 2010, xi, 772. ISBN 9780199206650. info
  • CSERMELY, Péter. Weak links : stabilizers of complex systems from proteins to social networks. 1st ed. Berlin: Springer, 2006, xix, 392. ISBN 3540311513. info
  • BARABÁSI, Albert-László. V pavučině sítí. Translated by František Slanina. Vyd. 1. V Praze: Paseka, 2005, 274 s. ISBN 8071857513. info
Teaching methods
Lectures, tutorial, home works.
Assessment methods
Colloqium requirements:
- At least 60 % attendance - Submission of Miniproject or Reader's Journal
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2023.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2025/IV124