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Complex Systems

 

Code: SCI3066

Extent: 20 - 25 credits

Language: English

Teacher in charge: Jari Saramäki

Target group: MSc students with sufficient prerequisite knowledge

Application procedure: Open for all students of Aalto University

Quotas and restrictions: No quotas

Prerequisites: Elementary university-level mathematics: calculus, linear algebra, probability and
statistics. Programming (knowledge of Matlab and/or Python will help).

 

Content and structure of the minor

The aim is to introduce the student to the computational and theoretical background that is necessary for a quantitative understanding of complex systems, from the human brain to a diversity of biological and social systems. The skills learned here are helpful for students considering interdisciplinary scientific careers, or, e.g. for industrial data scientist positions.

Structure of the minor

Code

Name

Credits

Compulsory courses

10

MS-E2115

Experimental and Statistical Methods in
Biological Sciences

 

5

CS-E5740

Complex Networks

5

Elective courses

10 - 15

Select as many courses as needed to fulfill the 20 - 25 credit requirement

CS-E4840

Information Visualization

5

CS-E5700

Hands-On
Network Analysis

5

CS-E5720

Work Course on Bayesian Analysis

2

CS-E4070 Special Course in Machine Learning and Data Science 5
CS-E3210 Machine Learning: Basic Principles 5

CS-E5745

Mathematical Methods for Complex Networks

5

CS-E5880

Modelling Biological Networks

 5-7

CS-E5755*

Nonlinear
Dynamics and Chaos*

 5*

CS-E5790

Computational Science

5

*The course is not lectured in 2017 - 2018

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