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Computational and visual network analysis

This course provides an introduction to the variety of analytical methods for relational data, i.e., graphs and networks. After finishing the course, the students should be able to choose and develop the most suitable visual network analytic technique for the given task.

Course information

Number of credits

5 credits

Given by

Department of Computer Science and Media Technology

Open to

Doctoral students at Swedish universities

Teaching language

English

Location

Distance

Next course occasion

Spring 2022

Study rate, or the equivalent

33%

Deadline for applications

March 21, 2022

Registration

Application to Kostiantyn Kucher, kostiantyn.kucher@lnu.se

Prerequisites

- Intermediate or advanced programming experience in any language (Python and JavaScript are a strong plus, but are not mandatory)
- English (spoken and written)
- Ability and readiness to participate in mandatory seminar and oral exam activities according to the course schedule (on-site or online by Zoom)

Teaching method

Lectures, assignments, seminars, and an oral exam

More about the course content

This course provides an introduction to the variety of analytical methods for relational data, i.e., graphs and networks. Such data types are applied for numerous tasks within computer science, software engineering, and other domains such as social sciences, bioinformatics, security, etc.

This course addresses three perspectives: 1) computational network analysis, e.g., automatic identification of the most influential nodes; 2) graph drawing for automatic layout of nodes and edges; and 3) information visualization for interactive representation and exploration of networks and associated data. After finishing the course, the students should be able to choose and develop the most suitable visual network analytic technique for the given task.

Syllabus: https://kursplan.lnu.se/kursplaner/syllabus-4DV809.pdf

The course is also given in Växjö.