Information on individual educational components (ECTS-Course descriptions) per semester

Degree programme: Master Sustainable Energy Systems
Type of degree: FH Master´s Degree Programme
Winter Semester 2021

Course unit title Programming Techniques
Course unit code 072722010301
Language of instruction German
Type of course unit (compulsory, optional) Compulsory
Semester when the course unit is delivered Winter Semester 2021
Teaching hours per week 2
Year of study 2021
Number of ECTS credits allocated Second Cycle (Master)
Number of ECTS credits allocated 3
Name of lecturer(s) Franz GEIGER

Prerequisites and co-requisites


Course content

This course covers the use of a multi-dimensional, numerical programming language (Python, Matlab) and a database language (SQL) on the basis of typical challenges in the field of energy technology (e.g. determination of the PV own consumption share). Particular attention is paid to the networking of engineering and programming perspectives.

  • Structured data: Data types, lists, vectors, matrices, dictionaries, GIS-data, arithmetic operations, (csv-)import/export
  • Fundamentals of programming: control structures, functions, procedures (subprograms), etc.
  • Basics of object-oriented programming: classes, objects, methods, attributes
  • Visualization: various plots possibly after previous preparation
  • Fundamentals of relational databases
  • Implementation in Python, Matlab and SQL

Learning outcomes

Students acquire fundamental knowledge and skills in technical programming and can apply them to scientific tasks. The students

  • can select data types suitable for their programming problems, import their input data into them, and export results to a suitable file format.
  • process raw data (aggregate, filter, etc.) and visualize it scientifically.
  • are able to structure all processing steps of their program into suitable classes/objects, control structures, functions and procedures and to implement these in a script language.
  • can read pseudo code and help files.
  • use the most important SQL statements to find and edit data from databases.
  • understand how to design small SQL databases efficiently and on-demand.

Planned learning activities and teaching methods
  • Lectures
  • Programming exercises
  • Coaching

Assessment methods and criteria
  • Delivery or presentation of exercises in small groups and/or individually
  • Oral final examination



Recommended or required reading
  • Markstaler, Markus (2019): Photovoltaik für Ingenieure. Theorie und Anwendung für dezentrale Energiesysteme mit Python. Books on Demand, Norderstedt.
  • Swaroop, C.H.: A Byte of Python: Deutsche Übersetzung. Zugang: [28.1.2020].
  • Meier, Andreas (2010): Relationale und postrelationale Datenbanken. 7. Auflage. Springer-Verlag.

Mode of delivery (face-to-face, distance learning)

Presence course. Students will be informed of the lecturer's attendance requirements before the start of the course.