2025/2026
Structural Analysis and Visualization of Networks
Type:
Mago-Lego
Delivered by:
Joint Department with Sberbank ‘Financial Technologies and Data Analysis’
Where:
Faculty of Computer Science
When:
3 module
Open to:
students of one campus
Instructors:
Alexandra Kogan
Language:
English
ECTS credits:
3
Contact hours:
40
Course Syllabus
Abstract
The course «Structural Analysis and Visualization of Networks» is dedicated to studying networks. Some examples of the networks are social networks, the Internet, molecules, transportation maps, parse trees. The course will cover models of network formation, statistical and structural analysis of networks and machine learning tasks on networks. Practical tasks include analysis and visualization of networks using Python.
Expected Learning Outcomes
- Knows terminology and basic notion of network science
- Understand principles of network structure
- Can analyze real world network data using Python
- Can visualize network data using Python
Course Contents
- Introduction
- Power law
- Random graphs
- Centralities
- Node similarities, Assortativity
- ML on graphs
- Graph embeddings
- Graph neural networks
- Knowledge graphs
Assessment Elements
- Домашняя работаAverage grade for several home assignments. Assignments contain coding tasks in Python.
- ПроектAnalyze a real-life network, solve ML task. Prepare presentation about it and defend in class.
Bibliography
Recommended Core Bibliography
- Network science, Barabasi, A.-L., 2019
Recommended Additional Bibliography
- Newman, M. (2010). Networks: An Introduction. Oxford University Press, 2010
- Wasserman, S., & Faust, K. (1994). Social Network Analysis : Methods and Applications. Cambridge: Cambridge eText. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=490515