data processing, data analysis, data science, R, Big Data
Abstract:
Introduction to advanced non-relational database systems. Characteristics of different types of data. Data processing tools used. Practical part of the training - familiarization with the working environment, applied examples of data processing from practice, advanced methods of presenting outputs. Students' own work on open data. Consultation sessions for term papers. Seminar paper submission and presentation.
Objectives:
The aim of the course is primarily to familiarize students with the tools for data processing and analysis, to test the most common options used in data processing, including advanced options for presenting the results of analyses. Students will then independently perform data analysis on data from existing open systems.