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Faculty of Technical Sciences

Subject: Introduction to data science (17.ESI056)

General information:
 
Category Professional-applicative
Scientific or art field Applied Computer Science and Informatics
ECTS 6

Mastering students with basic concepts of data science. Students should apply acquired knowledge in anaysis, study and solving real problems.

Acquisition of modern knowledge and skills in data science. The student is trained to analyze, study and solve real problems using the acquired knowledge.

Basic concepts of data science. Algorithms in data science. Application of mathematical statistics methods in data science. Statistical deriving conclusion. Statistical tests. Sampling correlation and regression. Modeling based on computer intelligence (artificial neural networks, decision trees, associative rules, fuzzy logic, support vector machine, genetic algorithm, etc.). Expert systems. Application of artificial intelligence methods in data science. Big data analysis. Predictions and evaluations. Classification. Application of data science in different fields. Analysis of concrete examples.

Lectures. Computer excercises. Consultations. The theoretical part of knowledge is exposed in the lectures. At the same time, practical part of knowledge is exposed in the computer excercises.

Authors Title Year Publisher Language
Marz, N., Warren, J. Big Data : Principles and best practices of scalable realtime data systems 2015 Manning Publications, New York English
M. Magdon-Ismail, Y. AbuMostafa Learning from Data 2012 AMLBook English
Berthold, M.R. Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications 2012 Springer English
Srinivas Sajja, P., Akerkar, R. Advanced Knowledge Based Systems : Models, Applications & Research 2010 TMRF e-Book English
ONeil C., Schutt R. Doing Data Science 2013 OReilly Media, Inc. English
Sean Gerrish How Smart Machines Think 2018 MIT Press English
Cotton R. Learning R 2013 O’Reilly Media, Inc. English
Ethem Alpaydin Introduction to Machine Learning 2004 MIT Press English
Course activity Pre-examination Obligations Number of points
Complex exercises Yes Yes 70.00
Theoretical part of the exam No Yes 30.00
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Prof. Aleksandar Kupusinac

Full Professor

Lectures

Asst. Prof. Dunja Vrbaški

Assistant Professor

Lectures

Assistant - Master Aleksandar Manasijević

Assistant - Master

Computational classes

Assistant - Master Bojana Dragaš

Assistant - Master

Computational classes

Assistant - Master Nebojša Gordić

Assistant - Master

Computational classes

Faculty of Technical Sciences

© 2024. Faculty of Technical Sciences.

Contact:

Address: Trg Dositeja Obradovića 6, 21102 Novi Sad

Phone:  (+381) 21 450 810
(+381) 21 6350 413

Fax : (+381) 21 458 133
Emejl: ftndean@uns.ac.rs

© 2024. Faculty of Technical Sciences.