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Complex Systems

Code: SCI3066

Extent: 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

NBE-E4030

Experimental and Statistical Methods in
Biological Sciences

 

5

CS-E5740

Complex Networks

5

Elective courses

15

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

CS-E4840

Information Visualization

5

CS-E5700

Hands-On
Network Analysis

5

CS-E5720

Work Course on Bayesian Analysis

2

CS-E40xx

Special
course in Machine Learning and Data Science

5

CS-E3210

Machine
Learning: Basic Principles

 5

CS-E5730

Mathematical
Modelling of Social Dynamics

 5

CS-E5750

Nonlinear
Dynamics and Chaos

 5

CS-L4090

Nonequilibrium Statistical Physics*

 7

*The course is not lectured in 2016-2017

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