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| Detailinformationen |
| Quellcurriculum |
Masterstudium Digital Energy Solutions 2026W |
| Lernergebnisse |
Kompetenzen |
| (*)The students can independently formulate algorithmic solutions for small to medium-sized energy-related tasks and implement them in Python programs.
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| Fertigkeiten |
Kenntnisse |
(*)Students can
- LO10: Develop simple algorithms and implement them in Python programs (K6)
- LO11: Use the common data types and instruction types provided by Python to implement Python programs (K3)
- LO12: Make correctness considerations based on dynamic tests (K4)
- LO13: Use structured data types (lists, tuples, sets, dictionaries) to model energy-related data (K3)
- LO14: Use libraries (e.g., numpy, matplotlib, pandas) for energy-related questions (K3)
- LO15: Apply the principle of exception handling to react to error situations (K3)
- LO16: Break programs down into functions (K3)
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(*)- LO1: Algorithmic thinking
- LO2: Simple data types
- LO3: Elementary input/output
- LO4: Structured data types (lists, tuples, sets, dictionaries)
- LO5: Statement types (assignments, expressions, branches, loops)
- LO6: Functions, parameter passing and return values
- LO7: Simple exception handling
- LO8: Selected libraries (e.g., numpy, matplotlib, pandas)
- LO9: Good programming style
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| Beurteilungskriterien |
(*)Written partial exams (theory questions, practical programming examples)
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| Lehrmethoden |
(*)The exercise session applies a blended learning format, i.e., lecture in class and distance learning. The students are provided in advance with the related material, which is accomplished in class. In addition, there is an accompanying exercise (Übung), which students attend in the same semester. In the exercise part (UE), students receive different tasks and examples (typical problems in software development and data analysis) to solve. This allows students to assess if they are able to apply their knowledge. Possible results of these tasks and examples are discussed in class. For specific topics, there are additional examples and tasks, which are solved together in class. Students have to possibility, to reflect and discuss problems in class.
Exercise:
- Reflection and deepening of lecture content using practical examples
- Assignment and discussion of exercises
- Presentation and discussion of solutions by students and instructors
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)- Course materials (presentation slides, tutorial examples, and solutions) are made available via Moodle
- Matthes E.: Python Crash Course (current edition), no starch press, San Francisco, USA
- Klein B.: Einführung in Python 3 für Ein- und Umsteiger (current edition), Hanser Verlag, München, Deutschland
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| Lehrinhalte wechselnd? |
Nein |
| Sonstige Informationen |
(*)It is expected that students have basic knowledge in the application of Windows/Mac/Linux and application programs as well as on how to organize directories and files. Students are required to attend the corresponding lecture during the same semester.
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