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Regular version of the site
Master 2021/2022

Network Science

Type: Elective course (Data Science)
Area of studies: Applied Mathematics and Informatics
When: 1 year, 3, 4 module
Mode of studies: offline
Open to: students of one campus
Instructors: Dmitrii Kiselev, Ilya Makarov, Leonid E Zhukov
Master’s programme: Data Science
Language: English
ECTS credits: 6
Contact hours: 78

Course Syllabus

Abstract

The course “Network Science” introduces students to new and actively evolving interdisciplinary field of network science. Started as a study of social networks by sociologists, it attracted attention of physicists, computer scientists, economists, computational biologists, linguists and others and become a truly interdisciplinary field of study. In spite of the variety of processes that form networks, and objects and relationships that serves as nodes and edges in these networks, all networks poses common statistical and structural properties. The interplay between order and disorder creates complex network structures that are the focus of the study. In the course we will consider methods of statistical and structural analysis of the networks, models of network formation and evolution and processes developing on network. Special attention will be given to the hands-on practical analysis and visualization of the real world networks using available software tools and modern programming languages and libraries.