Data processing

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Applied Informatics in Transportation

Synopsis:

Students will learn about tools for data processing and analysis, using practical examples to try out the most common options used in data processing, including advanced options for presenting the results of analyses. In advanced methods, students will also perform specific analysis using Bayesian networks. Students will then independently perform data analysis on data from existing open systems.

Requirements:

-

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

The aim of the course is primarily to familiarize students with tools for data processing and analysis, to test the most common options used in data processing, including advanced options for presenting analysis results.

Study materials:

Jan Rauch, Milan Šimůnek: Dobývání znalostí z databází, LISp-Miner a GUHA. Praha: Oeconomica VŠE, 2014.

Petr Berka: Dobývání znalostí z databází. Praha: Academia, 2003.

Irena Holubová, Karel Minařík, David Novák, Jiří Kosek: Big Data a NoSQL databáze.

Arun K. Somani, Ganesh Chandra Deka: Big Data Analytics. CRC Press, 2017.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• navaz. mag. PRE program IS v CZ 20/21 (nová akreditace) (compulsory course)
• navaz. mag. PRE program IS v EN 20/21 (nová akreditace) (compulsory course)
• navaz. mag. PRE program SC 20/21 (pro studenty, kteří absolvují některé předměty 1.roč. na UTEP) (compulsory course in the program)
• navaz. mag. PRE program IS joint degree 20/21 (nová akreditace) (compulsory course)
• navaz. mag. PRE program IS v CZ 21/22 (nová akreditace) (compulsory course)
• navaz. mag. PRE program IS v CZ 22/23 (nová akreditace) (compulsory course)
• navaz. mag. PRE program IS v CZ 23/24 (compulsory course)