Network Science

Master 2023/2024

Type: Elective course (Data Science)

Area of studies: Applied Mathematics and Informatics

Delivered by: School of Data Analysis and Artificial Intelligence

Where: Faculty of Computer Science

When: 1 year, 3, 4 module

Mode of studies: offline

Open to: students of one campus

Instructors: Alexandra Kogan, Vitaliy Pozdnyakov

Master’s programme: Data Science

Language: English

ECTS credits: 6

Contact hours: 78

Full 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.

Learning Objectives

To familiarize students with a new rapidly evolving filed of network science, and provide practical knowledge experience in analysis of real world network data.