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Data processing

Course Code:
14PD-E
Academic Degree:
master
Study Programme:
Intelligent Transport Systems (N1041A040006)
semesterlanguage
2english flag
Erasmus:
course for Erasmus and Exchange students in summer semester
Form of Study:
full-time
Credits:
6
Number of Hours:
2 + 4 hours per week - in full-time study
Type of Course:
obligatory
Course Completion:
credit, exam
Supervisor:
Ing. Mgr. Michal JEŘÁBEK, Ph.D.
Course Tutor:
 
roh  Lectures:
Ing. Martin Šrotýř, Ph.D.
Ing. Miroslav Vaniš, Ph.D.
roh  Training Course:
Ing. Martin Šrotýř, Ph.D.
Ing. Miroslav Vaniš, Ph.D.
Supervising Department:
Department of Applied Informatics in Transportation (16114)
Keywords:
Bayesian networks, data processing, data analysis
Abstract:
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.
Objectives:
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.