Department of Information and Computing Sciences

Departement Informatica Onderwijs
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Onderwijs Informatica en Informatiekunde

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Network science

Website:website containing additional information
Course code:INFOMNWSC
Credits:7.5 ECTS
Period:period 4 (week 17 through 26, i.e., 20-4-2020 through 26-6-2020; retake week 28)
Participants:up till now 1 subscriptions
Schedule:Official schedule representation can be found in Osiris
lecture          Erik Jan van Leeuwen
Johan van Rooij
Note:No up-to-date course description available.
Text below is from year 2018/2019
Network science is an exciting new field that studies large and complex networks, such as social, biological, and computer networks. The class will address topics from network structure and growth to the spread of epidemics. We study the diverse algorithmic techniques and mathematical models that are used to analyze such large networks, and give an in-depth description of the theoretical results that underlie them.

List of potential topics
Random graphs, giant components, percolation, spreading phenomena, basic algorithms for network science, lower bounds for polynomial-time problems, sampling algorithms, streaming algorithms, sublinear algorithms, power laws, spreading phenomena, community detection, graph partitioning algorithms.

The course assumes that you have basic skills in algorithms and mathematics. In particular, the course assumes familiarity with basic graph algorithms (shortest paths, flows), such as offered in Algoritmiek, and NP-completeness, such as offered in Algoritmiek or Algorithms for Decision Support. Having taken Algorithms and Networks is helpful, but not required.
Literature:May change!
A. Barabasi, Network Science, for free online
M.E.J. Newman, Networks, 2nd edition (2018).
Course form:The first part of the course will have two lectures a week and a tutorial. The second part consists of writing a term paper, peer reviewing, and a flash talk.
Exam form:Exam on studied chapters of the book, term paper, presentation, peer review. See the course webpage for details.
Minimum effort to qualify for 2nd chance exam:To qualify for the retake exam, the grade of the original must be at least 4.