Course: Introduction to Programming for IT 1

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Course title Introduction to Programming for IT 1
Course code KMI/ZPP1
Organizational form of instruction Seminar
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Laštovička Jan, Mgr. Ph.D.
  • Trnečka Martin, RNDr. Ph.D.
  • Zacpal Jiří, Mgr. Ph.D.
Course content
unspecified

Learning activities and teaching methods
Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
Student performance, Analysis of Activities ( Technical works)

Recommended literature
  • Hetland, M. L. (2014). Python algorithms: mastering basic algorithms in the Python language (2nd Edition).
  • Lutz, M. Learning Python, 5th edition.
  • Ramalho, L. (2015). Fluent Python: Clear, Concise, and Effective Programming (1st Edition).
  • Reitz, K., Schlusser, T. (2016). The Hitchhiker's Guide to Python: Best Practices for Development.
  • Summerfield, M. (2010). Python 3, výukový kurz.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Industrial Mathematics (2020) Category: Mathematics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Business Mathematics (2021) Category: Mathematics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Computer Science for Education (2024) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Data Science (2020) Category: Mathematics courses 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Information Technologies (2022) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Winter