Кто читает:: Базовая кафедра ПАО Сбербанк «Финансовые технологии и анализ данных»

Статус:: Курс по выбору

Когда читается:: 1-й курс, 3 модуль

Преподаватель

Коган Александра Сергеевна

Full Syllabus Ask Question

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.

Learning Objectives

To provide students with theoretical and practical knowledge of network science

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 работа
Average grade for several home assignments. Assignments contain coding tasks in Python.
Проект
Analyze a real-life network, solve ML task. Prepare presentation about it and defend in class.

Interim Assessment

2025/2026 3rd module
0.4 * Домашняя работа + 0.6 * Проект

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

Authors

Emasheva Valeriia Anatolevna

Магистерская программа «Финансовые технологии и анализ данных»

Контакты

Structural Analysis and Visualization of Networks