UCJDDAD1 Databanks and Datamining

Faculty of Philosophy and Science in Opava
Winter 2019
Extent and Intensity
1/0/0. 0 credit(s). Type of Completion: dzk.
Guaranteed by
Institute of Foreign Languages – Faculty of Philosophy and Science in Opava
Contact Person: Ferdinand Podpora
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The aim of the course is to introduce the students into the main terms and methods of discovering and learning about large databanks. The methods include neurocomputing, fuzzy set theory and fuzzy logic, statistical data assessment, and probability (statistical) methods as well as methods of acquiring qualitative findings and their evaluation. Current data mining systems are characterized, their methods and principles are explained and analyzed, and their practical use is discussed. Recommended literature: Marček, D., Marček, M.: Neuronové sítě a jejich aplikace. EDUS ŽU, 2006 Berka, P.: Dobývání znalostí z databází. Academia, Praha, 2003 Kecman, V.: Learning and Soft Computing - Support Vector Machines, Neural Networks and Fuzzy Logic Models. Massachusetts Institute of Technology, 2001 Hastie, T., Tibshirani, R., Friedman, J.: The Element sof Statistical Learning. Data Mining, Inference, and Prediction. Springer, 2001
Language of instruction
English
Further Comments
The course can also be completed outside the examination period.
The course is also listed under the following terms Winter 2007, Winter 2008, Winter 2009, Winter 2010, Winter 2011, Winter 2012, Winter 2013, Winter 2014, Winter 2015, Winter 2016, Winter 2017, Winter 2018, Winter 2020, Winter 2021.
  • Enrolment Statistics (Winter 2019, recent)
  • Permalink: https://is.slu.cz/course/fpf/winter2019/UCJDDAD1