Course unit code:
Course unit title:
Batch data processing
Mode of completion and Number of ECTS credits:
Exm (5 credits)
Course supervisor:
prof. Ing. Michal Kvasnica, PhD.
Name of lecturer(s):
M. Kvasnica, M. Wadinger (2023/2024 – Winter)
M. Kvasnica, M. Wadinger (2022/2023 – Winter)
Learning outcomes of the course unit:
Students are capable of designing a suitable data structure to store data in JSON, XML, and CSV textual formats. They know how to read, process and filter data stored in these formats and use them for further processing. Students master processing of JSON data in Python, JavaScript and Matlab programming languages. They know how to validate XML files using DTD and XML schema languages, and are capable of transforming them using the XSLT language. Students gain practical skills of reading and processing JSON, XML and CSV data using the Python's Pandas library. They are able to construct REST APIs based on these formats.
Prerequisites for registration:
Course contents:
Recommended or required reading:
  • BRADLEY, Neil. The XML companion. Addison-Wesley Professional, 2002.
  • GRUS, J.: Data Science from Scratch: First Principles with Python, ISBN 978-1491901427, O'Reilley
Planned learning activities and teaching methods:
Contact teaching: Lectures - 13 h Exercises - 39 h Contactless teaching: Preparation for lectures and exercises (study of literature, programming) - 20 h Work on assignments - 24 h Preparation of the final project - 29 h
Assesment methods and criteria:
Evaluation of continuous work at exercises contributes by 50% to the final grade. The remaining 50% can be earned by completing and defending the final project. The rating is based on the standard FCHPT scale.
Language of instruction:
Slovak, English
Facebook / Youtube

Facebook / Youtube