PřF:E3011 Algorithms and programs - Course Information
E3011 Algorithmization and programming
Faculty of ScienceSpring 2024
- Extent and Intensity
- 2/2/0. 4 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- Mgr. Jan Böhm (lecturer)
doc. Ing. Daniel Schwarz, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Schwarz, Ph.D.
RECETOX – Faculty of Science
Contact Person: Mgr. Jan Böhm
Supplier department: RECETOX – Faculty of Science - Timetable
- Mon 19. 2. to Sun 26. 5. Wed 14:00–17:50 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
- Biomedical bioinformatics (programme PřF, B-MBB)
- Epidemiology and modeling (programme PřF, B-MBB)
- Mathematical Biology (programme PřF, B-EXB)
- Course objectives
- 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) - Syllabus
- 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.
- Literature
- Buchalcevová, A.: Algoritmizace a programování. Praha: VŠE, 1994.
- Topfer, P.: Algoritmy a programovací techniky. Praha: Prometheus, 1995.
- Virius, M.: Základy algoritmizace. Praha: ČVUT, 1997.
- Teaching methods
- Lectures, excersises - creating algorithms that solve given problems and implementing them in Python, homeworks, project.
- Assessment methods
- 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.
- Enrolment Statistics (Spring 2024, recent)
- Permalink: https://is.muni.cz/course/sci/spring2024/E3011