Name Cr Method of study Time Location Organiser
Network Analysis 5 Cr Lecture Course 19.1.2021 - 4.3.2021
Network Analysis 5 Cr Lecture Course 14.1.2020 - 27.2.2020
Network Analysis 5 Cr Lecture Course 15.1.2019 - 28.2.2019

Target group

Data Science Master's Programme is responsible for the course.

The course belongs to Specialization Studies > Al­gorithmic Data Sci­ence.

Elective course with permanent offering.

The course is available to students from other degree programmes.


Prerequisites in terms of knowledge

Basic data structures and algorithms. Some experience in a modern programming language

Prerequisites for students in the Data Science programme, in terms of courses


Prerequisites for other students in terms of courses


Recommended preceding courses

CSM12101 Design and Analysis of Algorithms

Learning outcomes

Students will learn to:

  • use algorithms to measure basic quantities (e.g., centrality measures) associated with networks;
  • describe network phenomena (e.g., the spread of epidemic diseases and the propagation of information in social networks) in terms of basic network models;
  • use algorithms to predict the effect of network phenomena.


Recommended for 1st year of Master's studies.

The course will be offered in the spring term (period 3), every year.


The course will cover the following topics: basics of graph theory; network embeddings; network formation mechanisms; information cascades and epidemics; population models, power laws, and rich-get-richer phenomena; the small-world phenomenon.

Activities and teaching methods in support of learning

The course will be centered around lectures delivered by the instructors.

Study materials

The course follows the book "Networks, Crowds, and Markets: Reasoning About a Highly Connected World" by David Easley and Jon Kleinberg, with emphasis on Parts I, IV, V and VI.

A full-draft copy of the book can be obtained from the website of the book at

Assessment practices and criteria

The students will complete homework assignments and a project.

Recommended optional studies

CSM12101 Design and Analysis of Algorithms

Completion methods

All course material will be available online for students of the course, but it is strongly recommended that students attend the lectures.
No strict attendance requirements.

Students must complete a minimum of grades to pass the course.