E3011 Algorithmization and programming

Faculty of Science
Spring 2026
Extent and Intensity
2/2/0. 4 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
Mgr. Jan Böhm (lecturer)
prof. Ing. Daniel Schwarz, Ph.D. (lecturer)
Mgr. Barbora Zwinsová, Ph.D. (assistant)
Mgr. Barbora Halaštová (assistant)
Guaranteed by
prof. Ing. Daniel Schwarz, Ph.D.
RECETOX – Faculty of Science
Contact Person: Mgr. Jan Böhm
Supplier department: RECETOX – Faculty of Science
Timetable
Mon 16. 2. to Fri 22. 5. Wed 13:00–16:50 D29/347-RCX2
Prerequisites
High-school math. Propositional calculus. If you can understand this, your english is good enough.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Abstract
The aim of the course is to provide students with basic concepts of programming and algorithmization using diagrams, pseudocode and examples in the programming language Python.
Learning outcomes
After completion of the course, student will be able:
- read flowcharts and pseudocode;
- come up with an algorithm that solves given task;
- produce readable code;
- use basic programming constructs (cycles, if-else, recursion, function);
- code in Python (basics)
Key topics
  • 1. Every-day algorithms. Turtle graphics. Flowcharts, pseudocode. Cycles and funcions.
  • 2. Sequences. If-else. Recursion. Application in algebra, numerical methods and models.
  • 3. Vector and matrix algebra. Transformations in plane. Determinant and its applications.
  • 4. Randomness. Difficult probability problems. Board games.
Study resources and literature
  • MATTHES, Eric. Python crash course : a hands-on, project-based introduction to programming. 2nd edition. San Francisco: No Starch Press, 2019, xxxvi, 506. ISBN 9781593279288. info
  • SKIENA, Steven S. The algorithm design manual. Second edition. London: Springer, 2008, xvi, 730. ISBN 9781848000698. info
  • CORMEN, Thomas H. Introduction to algorithms [2nd ed.]. 2nd ed. Cambridge: MIT Press, 2001, xxi, 1180. ISBN 0-262-03293-7. info
Approaches, practices, and methods used in teaching
Lectures, excersises - creating algorithms that solve given problems and implementing them in Python, homeworks, project.
Method of verifying learning outcomes and course completion requirements
3 tasks in the course of the semester. All must be hand over and total of at least 50 % must be achieved.
Written test at the end of the semester. Two parts: with and without PC. All notes, books and own codes can be used. You need to score more then 2/3 of possible points.
Project (in group or alone). During presentation you need to explain how your solution works and show that your code works as well.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (recent)
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