Admission requirements
Prerequisites include the course Essentials of Mathematics, Data Science, and Programming and Introduction to Network Science (or their equivalent).
Description
The purpose of this course is to provide a general overview of the structural properties of networks and how we can quantify and abstract properties of networks that determine their behavior at different scales, including applications drawn from different fields. Topics that will be covered include:
Network components, shortest paths, and the small world property
Degree distributions, power laws, and scale free networks
Clustering coefficients, cliques (and community structures)
Random graphs and random networks
Models of network formation and growth
Course Objectives
The primary objectives of this course are for students to learn the basics of how we model and classify structural properties of networks and how these might apply to real world examples. By the end of this course, the student will be equipped with the tools to independently analyze networks based on their statistical properties, and be able to understand and follow most applications of network analyses encountered in the literature.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Mode of Instruction
Lecures and problem sessions
Assessment method
20% in class quizzes/ exercises, 80% final oral presentation/ exam
Reading list
Networks by M.E.J. Newman
Registration
tbd
Contact
Diego Garlaschelli, Subodh Patil, Alberto Ceria
Remarks
part of the minor Network Science for a Connected World