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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

15

Becs-114.5501

Experimental and Statistical Methods in
Biological Sciences I

X

5

BECS-E2601

Bayesian Data Analysis

5

Becs-114.4150

Complex Networks

5

Elective courses

10

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

T-61.5010

Information Visualization

5

BECS-E4200

Hands-On
Network Analysis

5

Becs-114.5312

Work Course on Bayesian Analysis

2

Becs-114.4610

Special
course in Bayesian modeling I

5

T-61.3050

Machine
Learning: Basic Principles

 5

Becs-E4101

Mathematical
Modelling of Social Dynamics

 5

Becs-114.7151

Nonlinear
Dynamics and Chaos

 5

Becs-L4072

Nonequilibrium Statistical Physics

 7

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