Delivered at:: School of Data Analysis and Artificial Intelligence

Course type:: Elective course

When:: 4 year, 1, 2 module

Instructor

Fernique, Тhomas C.

Full Syllabus

Abstract

Graphs are abstract structures used to model pairwise relations between objects. They are used in various context as physical, biological, social or information systems. Many practical problems can indeed be represented by graphs (often called networks in this context). These practical problems raise many theoretical questions and make graphs a very active field of study in discrete mathematics today.

Learning Objectives

The goal of this course is to acquire the fundamentals of graph theory, to benefit from an overview of the main classical results, and to put them into practice during the seminars (at the blackboard or on the computer).

Expected Learning Outcomes

Can easily learn about a specific subject
Apply their knowledge

Course Contents

Fundamental concepts
Graph drawing
Planarity
Random graphs
Coloring

Assessment Elements

Homework
Article presentation
Exam

Interim Assessment

2024/2025 2nd module
(Exam+Homework+Presentation)/3

Bibliography

Recommended Core Bibliography

Introduction to graph theory, West, D. B., 2001
Network science, Barabasi, A.-L., 2019

Recommended Additional Bibliography

Random graphs, Bollobas, B., 2001

Authors

FERNIK Toma Kleman Kleman
Антропова Лариса Ивановна

Bachelor’s Programme 'Applied Mathematics and Information Science'

Applied Graph Theory