Daten
Offizielle Daten in der Fachveröffentlichung für das folgende akademische Jahr: 2023-2024
Lehrbeauftragte/r
-
András MATUZ
research associate professor,
Department of Behavioural Sciences -
Semesterwochenstunden
Vorlesungen: 3
Praktika: 9
Seminare: 0
Insgesamt: 12
Fachangaben
- Kode des Kurses: OPF-PPK-T
- 1 kredit
- Pharmacy
- Optional modul
- spring
OPA-M1E-T completed
Zahl der Kursteilnehmer für den Kurs:
min. 5 – max. 15
Thematik
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.
Vorlesungen
- 1. The Python programming language - Dr. Matuz András
- 2. Installation and modules - Dr. Matuz András
- 3. Basic programming concepts - Dr. Matuz András
Praktika
- 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
Seminare
Materialien zum Aneignen des Lehrstoffes
Obligatorische Literatur
Vom Institut veröffentlichter Lehrstoff
The study material required for preparation will be posted on Neptun/TEAMS after the presentation
Skript
Empfohlene Literatur
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
Voraussetzung zum Absolvieren des Semesters
Maximum of 25 % absence allowed
Semesteranforderungen
Written test in the last lesson (solving a programming task), homework (programming project)
Möglichkeiten zur Nachholung der Fehlzeiten
To be discussed with the instructor.
Prüfungsfragen
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.
Prüfer
Praktika, Seminarleiter/innen
- Dr. Matuz András