Course title:

Complex networks

Primary programme:

Fizikus mérnök BSc

ECTS credits:

4

Course type:

compulsory

Number of lectures per week:

2

Number of practices per week:

1

Number of laboratory exercises per week:

0

Further knowledge transfer methods:

project work

Grading:

Examination

Special grading methods:

Project and homework

Semester:

5

Prerequisites:

Probability theory

Responsible lecturer:

Dr. János Török, associate professor, PhD

Lecturers and instructors:

Course description:

This course describes the most important models and measures of the complex network frameworks and aims the students to apply them effectively to problems of diverse origin.
Subjects:
Graph theory
Random graphs, Erdős-Rényi and Watts-Strogatz
Preferential attachment and scale freeness
Block and growth models
Link prediction
Random walks on graphs
Temporal networks, motifs, burstiness
Spreading on networks, mean field solutions
Robustness, cascades
Communities and algorithms
Core-periphery
Hierarchy
Sampling

Reading materials:

Newman, Mark Ed, Albert-László Ed Barabási, and Duncan J. Watts. The structure and dynamics of networks. Princeton university press, 2006. ISBN-13: 978-0691113579
http://networksciencebook.com/
Newman, Mark EJ. "Communities, modules and large-scale structure in networks." Nature physics 8, no. 1 (2012): 25-31. ISBN-13: 978-0199206650

List of competences:

Please find the detailed list, as quoted from the Hungarian training and outcome requirements of the Physicist Engineer program, in the Hungarian version of the course description.