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270148 PR Programmieren in C/Fortran/Python (2025S)
Prüfungsimmanente Lehrveranstaltung
Labels
GEMISCHT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Di 04.02.2025 08:00 bis Di 25.02.2025 23:59
- Abmeldung bis Di 25.02.2025 23:59
Details
max. 15 Teilnehmer*innen
Sprache: Deutsch
Lehrende
Termine
Zur Zeit sind keine Termine bekannt.
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
The final grade will be composed of three exercise reports (20% each), a short presentation of the programming project (20%), and class participation (20%).
Mindestanforderungen und Beurteilungsmaßstab
Attendance is compulsory (at least 50% of all dates).The final grade is given by this key:
100-87.5 Grade 1 "Sehr gut" ("excellent")
87.0-75.0 Grade 2 "Gut" ("good")
74.5-62.5 Grade 3 "Befriedigend" ("satisfactory")
62.0-50.0 Grade 4 "Genügend" ("sufficient")
49.5-0.0 Grade 5 "Nicht genügend" ("failed")
100-87.5 Grade 1 "Sehr gut" ("excellent")
87.0-75.0 Grade 2 "Gut" ("good")
74.5-62.5 Grade 3 "Befriedigend" ("satisfactory")
62.0-50.0 Grade 4 "Genügend" ("sufficient")
49.5-0.0 Grade 5 "Nicht genügend" ("failed")
Prüfungsstoff
Students will need to write short reports or documentation during the units (or at home) for some of the programming exercises. They will also need to conduct a small programming project (with either a provided or self-chosen topic) that they need to document and present to the other students.
Literatur
Introductory books on programming in general and on C/Fortran/Python.
More detailed literature suggestions and material will be provided via Moodle.
More detailed literature suggestions and material will be provided via Moodle.
Zuordnung im Vorlesungsverzeichnis
CH-TPA-05, WD4
Letzte Änderung: Di 28.01.2025 14:46
Learn basic concepts and skills in programming in C, Fortran, and/or Python for research-driven programming tasks (like data analysis, optimization, or numerical simulation) in different areas of chemistry.Content:
1 Basics of programming in C, Fortran, and Python
- input and output
- variables, data types, data structures
- flow control, conditionals, loops
- functions, modules, objects, classes
2 Selected algorithms, e.g.,
- recursion, search algorithms
- dynamic programming
3 Numerical algorithms, e.g.,
- linear algebra
- differential equation solvers
- Monte Carlo-style algorithms
4 Programming student projectMethods:
In-presence computer exercises with lecture-style introductions, guided analysis/discussion of code, and independent programming exercises.
Students will also write brief reports, documentation, and a short presentation.
The classes will be organized through Moodle.Students need not know all three programming languages at the beginning of the course. The first part of the course will give an overview over basic programming knowledge (concepts), but some previous knowledge is recommended.