Complex Networks

Data is displayed for academic year: 2023./2024.

Lecturers

Prof.
Mile Šikić
Prof.
Vedran Podobnik

Exercises

Filip Tomas
univ. mag. ing. el. techn. inf.
Asst. Prof.
Martina Antonić
Josipa Lipovac
univ. mag. ing. comp.

Course Description

The course is an introduction to the science of complex networks and their applications. Topics to be covered include the graph theory, data analysis, and applications to biology, sociology, technology, and other fields. Students will learn about the ongoing research in the field, and ultimately apply their knowledge to conduct their own analysis of a real network data set of their choosing as part of the final project.

Study Programmes

University graduate
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[FER3-HR] Control Systems and Robotics - profile
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[FER3-HR] Data Science - profile
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[FER3-HR] Electronics - profile
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[FER3-HR] Information and Communication Engineering - profile
Elective Courses (3. semester)
Elective Coursesof the Profile (3. semester)
[FER3-HR] Network Science - profile
Core-elective courses (3. semester)
[FER3-HR] Software Engineering and Information Systems - profile
Elective Courses (3. semester)

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

Exercises

Coding tutorials

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Attendance 10 % 20 % 10 % 20 %
Final Exam: Written 0 % 80 %
Exam: Written 0 % 80 %

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

Literature

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

For students

General

ID 252364
  Winter semester
5 ECTS
L0 English Level
L1 e-Learning
30 Lectures
0 Seminar
12 Exercises
0 Laboratory exercises
0 Project laboratory
0 Physical education excercises

Grading System

86 Excellent
74 Very Good
62 Good
50 Sufficient

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