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Terminated in academic year 2023/2024

Data Analysis II

Type of study MasterFollow-up Master
Language of instruction English
Code 460-4072/02
Abbreviation MAD II
Course title Data Analysis II
Credits 4
Coordinating department Department of Computer Science
Course coordinator doc. Mgr. Miloš Kudělka, Ph.D.

Subject syllabus

Lectures:
1. Network construction from vector data
2. Network clustering I, matrix algorithms
3. Network clustering II, graph partitioning (Kernighan-Lin)
4. Network sampling
5. Advanced network models I, generating of community structure
6. Advanced network models II, evolving networks
7. Community detection
8. Modularity and community structure
9. Correlation in networks
10. Network resilience and spread phenomena
11. Temporal networks
12. Multilayer networks I, properties and measures
13. Multilayer networks II, random walks and projections
14. Visualization of network data

Seminars are directly connected to the lectures, discussions and knowledge verification using experiments on data sets.

Literature

1. Mohammed J. Zaki, Wagner Meira, Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge University Press, May 2014. ISBN: 9780521766333 .
2. Jure Leskovec, Anand Rajaraman, David Ullman, Mining of Massive Datasets, 2nd editions, Cambridge University Press, Novemeber 2014, ISBN: 9781107077232 , On-line http://infolab.stanford.edu/~ullman/mmds/book.pdf [2014-09-12]

Advised literature

1. Mohammed J. Zaki, Wagner Meira, Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge University Press, May 2014. ISBN: 9780521766333 .
2. Jure Leskovec, Anand Rajaraman, David Ullman, Mining of Massive Datasets, 2nd editions, Cambridge University Press, Novemeber 2014, ISBN: 9781107077232 , On-line http://infolab.stanford.edu/~ullman/mmds/book.pdf [2014-09-12]


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