Complex Networks

Learning Outcomes

  1. Explain basic concepts of complex networks
  2. Apply the knowledge gained to real networks
  3. Analyze data gathered from social networks

Forms of Teaching

Lectures

Lectures

Laboratory

Week by Week Schedule

  1. Definition, Terms
  2. Erdos-Renyi random graphs, tree structure, giant component, Small-world (Watts-Strogatz) model
  3. Degree distributions
  4. Clustering
  5. Algorithms for computing degree distributions and clustering coefficients
  6. Network growth, preferential attachment, Barabasi-Albert model, power-law networks
  7. Centrality
  8. Not held
  9. Extremal paths and breadth-first search, maximum flows and minimum cuts, spanning trees
  10. Graph partitioning, community detection
  11. Spectral properties of adjacency matrix
  12. Structure of social network graphs
  13. Social network analysis
  14. Social network analysis
  15. Not held

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (3. semester)
Computer Engineering (profile)
Elective Courses of the Profile (3. semester)
Computer Science (profile)
Free Elective Courses (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (3. semester)
Data Science (profile)
Elective Courses of the Profile (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (3. semester)
Electronics (profile)
Free Elective Courses (3. semester)
Information and Communication Engineering (profile)
Elective Coursesof the Profile (3. semester)
Network Science (profile)
Core-elective courses (3. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (3. semester)

Literature

(.), Network Science, Albert-László Barabási,
(.), Networks – an Introduction, Mark Newman, Oxford University Press,

For students

General

ID 222622
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures
9 Laboratory exercises

Grading System

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Good
Acceptable