2026/2027
Анализ сетевых структур
Статус:
Маго-лего
Где читается:
Факультет компьютерных наук
Охват аудитории:
для своего кампуса
Преподаватели:
Поздняков Виталий Витальевич
Язык:
русский
Кредиты:
6
Контактные часы:
78
Программа дисциплины
Аннотация
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.
Цель освоения дисциплины
- To familiarize students with a new rapidly evolving filed of network science, and provide practical knowledge experience in analysis of real world network data.
Планируемые результаты обучения
- Know basic notions and terminology used in network science
- Understand fundamental principles of network structure and evolution.
- Can develop mathematical models of network processes.
- Can analyze real world network data.
Содержание учебной дисциплины
- Introdiction to network science
- Scale-free networks
- Random networks
- Network models
- Node centrality and ranking on networks
- Structural properties of networks
- Community detection in networks
- Epidemics on networks
- Cascades and influence maximization
- Node classification
- Link prediction
- Graph embedding
- Graph neural networks
- GNNs in practice
- Theoretical foundations of GNNs
- Knowledge graphs
Промежуточная аттестация
- 2026/2027 4th module0.25 * Экзамен + 0.33 * Тест + 0.17 * Домашнее задание + 0.17 * Соревнование + 0.08 * Индивидуальный проект
