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Advanced Data Analysis

Summary

This course provides the students, in its first part, necessary information about basic and advanced algorithms, typical algorithmic problems and their complexity. This part will also contain the introduction of programming techniques and programming and scripting languages. Next, foundations of vector data and network data analysis will be presented including simple algorithms used in both areas. The students will also be familiarized with different tools and libraries suitable for the solution of everyday tasks, primarily focused on biomedical data analysis.

Literature

• Levitin, A. (2012). Introduction to the design & analysis of algorithms. Boston: Pearson.
• Witten, I. H., Frank, E., Hall, M. A., Pal, C. J. (2016). Data Mining: Practical machine learning tools and techniques (Fourth Edition). Morgan Kaufmann Series in Data Management Systems.

Advised literature

• Libeskind-Hadas, R., Bush, E. (2014). Computing for biologists: Python programming and principles Cambridge University Press.
• Barabási, A. L. (2016). Network science. Cambridge university press.


Language of instruction čeština, angličtina
Code 460-6031
Abbreviation PAD
Course title Advanced Data Analysis
Coordinating department Department of Computer Science
Course coordinator doc. Mgr. Miloš Kudělka, Ph.D.