Curriculum on Self-Organizing Networked Systems

Curriculum

Core Courses

The following courses are mandatory:

Introduction to Self-Organizing Networked Systems

• Part I: What is a self-organizing system? Methodology and theory. Links to following courses.
• Part II: Case studies. A ring lecture with speakers from different universities and different fields.

Dynamic Systems

Lecture and Lab

Content: similar to "Nonlinear Dynamics and Chaos" by Steven H. Strogatz

Network Theory

Lecture and Exercises

Content: Networks from the real world. Network topology: Graph theory basics, random graphs, phenomena small wold and scale-freeness. Network functions/processes/algorithms: E.g. search, percolation.

Information Theory and Coding

Lecture and Exercises

Advanced Stochastics

Lecture and Exercises

Content: Selected topics from the following fields: Stochastic Processes. Statistical Physics.

Intelligent Systems (?)

Content: Game theory, neural networks, machine learning

Catch-up Courses

Depending on the background of the student, she or he attends a subset of the following courses:

Group Work

Group 1: Bauschert, Bettstetter, Pletzer, Quaritsch, Yanmaz

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Group 2: Anton, Manfred, Felix, Johannes,Alain

All courses should specifically deal with applications towards SOS.

Curriculum table

Subject	Type	g1 grad	g2 und.grad	g2 grad	g2 grad spec.	g3	g4
Dynamical Systems	Lecture			X
Information Theory	Lecture			X
Algorithms 1	Lecture & Lab			X
Algorithms 2	Lecture & Lab			X
Numerical Simulations	Lecture & Labs			X
Topics course SO in nature/society	Lecture			X
specified classes (choose two)
Network 1					X
Network 2					X
Statistical physics 1 & 2					X
Embedded Systems					X
Sensors and Robotics					X
Undergraduate
Calculus 1 & 2	Lecture		X
Statistics	Lecture		X
Diff. Equations	Lecture		X
Linear Algebra	Lecture		X
Programming	Lecture		X
Natural sciences	Lecture		X