Course unit code:
Course unit title:
Batch data processing
Mode of delivery, planned learning activities and teaching methods:
lecture – 1 hour weekly (on-site method)
seminar – 3 hours weekly (on-site method)
Credits allocated:
Recommended semester:
Automation and Information Engineering in Chemistry and Food Industry – master (full-time, attendance method), 3. semester
Level of study:
Prerequisites for registration:
Assesment methods:
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.
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
Language of instruction:
Slovak, English
Name of lecturer(s):
M. Kvasnica, M. Wadinger (2023/2024 – Winter)
M. Kvasnica, M. Wadinger (2022/2023 – Winter)
Course supervisor:
prof. Ing. Michal Kvasnica, PhD.
Last modification:
14. 9. 2021

Department of Information Engineering and Process Control
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