Official data in SubjectManager for the following academic year: 2023-2024
research associate professor,
Department of Behavioural Sciences
Number of hours/semester
lectures: 3 hours
practices: 9 hours
seminars: 0 hours
total of: 12 hours
- Code of subject: OAF-PPK-T
- 1 kredit
- General Medicine
- Optional modul
Course headcount limitations
min. 5 – max. 15
The Python programming language is one of the most widely used programming languages, which is also due to the fact that the use of the language can be easily learned even by people without programming experience. This course introduces the fundamentals of programming through the Python language, including data types, loops, functions, objects, and more. During the exercises, we review the use of the most popular modules (e.g. Numpy, Pandas, Scipy) and demonstrate their practical application through medical and psychological examples. The aim of the course is for students to be able to solve problems with the help of programming primarily in the fields of data management, statistics, data presentation and experimental design.
- 1. The Python programming language - Dr. Matuz András
- 2. Installation and modules - Dr. Matuz András
- 3. Basic programming concepts - Dr. Matuz András
- 1. Creating variables, data types and calculations
- 2. Lists and dictionaries
- 3. Built-in functions and Loops
- 4. If-statements: let's write a conversational program!
- 5. Writing simpler programs: creating unit converter, number system converter and poem generator programs
- 6. Vectors, matrices, and scientific functions (SciPy, Numpy)
- 7. Data analyis with Pandas
- 8. Programming of reaction time-based experiments (Psychopy)
- 9. Test
Literature developed by the Department
The study material required for preparation will be posted on Neptun/TEAMS after the presentation
Mark Summerfield (2009) Python 3 programozás: átfogó bevezetés a Python nyelvbe
Hall, T., & Stacey, J. P. (2010). Python 3 for absolute beginners.
Hans Petter Langtangen (2014) A Primer on Scientific Programming with Python
Conditions for acceptance of the semester
Maximum of 25 % absence allowed
Written test in the last lesson (solving a programming task), homework (programming project)
Making up for missed classes
To be discussed with the instructor.
Written test in the last class. The test can be repeated twice in the first two weeks of the exam period in order to improve the grade. Submission of project work.
Instructor / tutor of practices and seminars
- Dr. Matuz András