Oct 22, 2020   12:42 p.m. Sergej
Academic information system

Course syllabus I1-DM - Data mining (FCE - WS 2020/2021)


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University: Slovak University of Technology in Bratislava
Faculty:
Course unit code:
I1-DM
Course unit title:
Data mining
Mode of delivery, planned learning activities and teaching methods:
lecture
2 hours weekly (on-site method)
seminar
2 hours weekly (on-site method)

 
Credits allocated: 5
 
Recommended semester/trimester: Mathematical and Computational Modeling - master (semi-compulsory), 3. semester
Level of study:
2.
Prerequisites for registration:
none
 
Assesment methods:
successful elaboration of given tasks, minimum 56 points at exam
 
Learning outcomes of the course unit:
Data mining is the computational process of discovering patterns in large data
sets. It is used on universities as well as in practice (marketing, business,
medicine, large data warehouses management ...) and it utilizes the methods of
statistics, machine learning and artificial intelligence to solve real world
problems. A student will get an overview of fundamental techniques, from
theoretical background to typical applications. Upon completion he will be
able to find a solution of many real world problems by means of the open
source software environment - R.
 
Course contents:
- Cluster analysis (hierarchical clustering, k-means algorithm).
- Networks analysis.
- Classification and regression (logistic regression, linear discriminant
analysis, nearest neighbor method, naive Bayes classifier, support vector
machines, decision trees, neural networks).
- Ensemble methods (random forests, AdaBoost, stacking, GBM).
- Anomalies detection.
- Recommender systems.
- Data mining of texts, images, audio files, web, spatial and time series.
- Big data analysis.
- Visualization techniques.
 
Recommended or required reading:
Basic:
WILLIAMS, G. Data Mining Desktop Survival Guide.  [online]. 2010. URL: http://datamining.togaware.com/survivor/index.html.
RUD, O P. Data Mining: Praktický průvodce dolováním dat pro efektivní prodej, cílený marketing a podporu zákazníků (CRM). Praha : Computer Press, 2001. 322 p. ISBN 80-7226-577-6.
TORGO, L. Data mining with R: Learning with Case Studies. Boca Raton : CRC Press, 2011. 289 p. ISBN 978-1-4398-1018-7.

 
Language of instruction:
slovak or english
 
Notes:
 
Courses evaluation:
Assessed students in total: 6

A
B
C
D
EFX
33,3 %
16,7 %33,3 %
16,7 %
0 %
0 %
Name of lecturer(s):
doc. Ing. Tomáš Bacigál, PhD. (examiner, instructor, lecturer, tutor) - slovak, english
prof. RNDr. Karol Mikula, DrSc. (person responsible for course)
Mgr. Miroslav Sabo, PhD. (instructor) - slovak
 
Last modification:
4. 6. 2019
Supervisor:
prof. RNDr. Karol Mikula, DrSc. and programme supervisor


Last modification made by Ing. Peter Korčák on 06/04/2019.

Type of output: