Terminated in academic year 2022/2023

Advanced Methods for Data Analysis

Type of study	Follow-up Master
Language of instruction	Czech
Code	460-4128/01
Abbreviation	PMAD
Course title	Advanced Methods for Data Analysis
Credits	4
Coordinating department	Department of Computer Science
Course coordinator	prof. Ing. Jan Platoš, Ph.D.

Subject syllabus

Lectures:
1. Big data
2. Sampling methods
3. Dimension Reduction algorithms
4. Aggregation and clustering on big data
5. Advanced algorithm for data classification
6. Ensemble classification algorithms
7. Deep Models, Deep Neural Networks
8. Deep model learning algorithms
9. Recommender systems
10. Data Visualization

Excercise:
Practical evaluation of the theory on real-world datasets.

Literature

Ian H. Witten, Eibe Frank, Mark A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, Morgan Kaufmann, 2011, ISBN: 978-0123748560
Charu C. Aggarwal, Data Mining - The Text Book, Springer 2015.

Advised literature

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

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