IV124 Complex Networks

Faculty of Informatics
Spring 2026
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, Ph.D. (lecturer)
RNDr. Jan Fousek, Ph.D. (lecturer)
Guaranteed by
RNDr. Josef Spurný, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Contact Person: RNDr. Josef Spurný, Ph.D.
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
there are 40 fields of study the course is directly associated with, display
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
  • 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. Linked :how everything is connected to everything else and what it means for business, science, and everyday life. New York: Plume Book, 2003, 294 s. ISBN 0-452-28439-2. info
Teaching methods
The course will be conducted in the form of a regular two-hour seminar. The two-hour in-person session will be divided into a theoretical lecture and practically-oriented part. The practical part will focus on demonstrations of tools and practical examples related to the covered material; in the second half of the semester, it will also include consultations for ongoing student projects. Students choose their projects based on their (academic) interests and field of study. Independent work is allowed as well as collaboration in small groups (assessed individually based on the project's complexity, with a maximum of 3 members). As part of the project, students will analyze a real dataset, either freely available (e.g., see here: http://www-personal.umich.edu/~mejn/netdata/) or obtained independently as part of the project (which increases the workload and allows for the involvement of more students). A written project report is required as well as short presentation as part of the colloqium at the end of the semester. The focus of the course is shifted towards the ability to practically apply network analysis across various target fields.
Assessment methods
Colloqium requirements:
- At least 60 % attendance on seminars - Submission of individual or team project
Language of instruction
English
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, Spring 2025.
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