Introduction to Computational Methods (not only) for Engineers
Computational methods have become indispensable tools in modern engineering (and R&D in general), revolutionizing the way engineers design, analyze, and optimize complex systems. With the advent of powerful computers and advanced algorithms, engineers can now simulate and model intricate phenomena that were once challenging to comprehend. These methods encompass a wide range of disciplines, including finite element analysis, optimization techniques, and machine learning. Although computational methods offer numerous advantages (not only) to engineering, they necessitate a proficiency in advanced skills from their users. This short course offers an illuminating introduction to a range of essential computational methods, serving as a valuable resource for students’ studies and paving the way for more advanced courses.
Organizational Info (Summer term 2024)
| (Lecture-style) Introductions | Hands-on Exercises | |
|---|---|---|
| Start | 08.05.2024 | 08.05.2024 |
| Time | Wednesday, 9:00 to 10:00 | Wednesday, 10:00 to 12:00 |
| Room | MB I E23/24 | MB I E23/24 |
| Lecturers / Tutors | Moritz Schulze Darup, Matthias Faes | |
| Moodle | Link to the course | |
| Language | English | |
Content
From the wide range of computational methods in engineering, the course covers the following six topics using concise exercises and small projects (3 h each):
- Introduction to Matlab and proper coding hygiene
- Data visualization: Graphs, surface plots, and visualizing multidimensional datasets
- Data analysis: Fourier transformation, regression, error bars
- Simulation: First encounter with computer-assisted analysis of simple ODEs and PDEs
- Optimization: Applying and analyzing linear programming
- Machine learning: Supervised and unsupervised using neural networks and clustering
For each topic, the students will learn fundamental challenges, strategies for solving them, and suitable computational tools. The course is designed for an early stage of study and it offers two credit points (2 CP) in the framework of non-disciplinary competences (in German: außerfachliche Kompetenz). The course is jointly offered by the chairs of Control and Cyberphysical Sytems (RCS) and Reliability Engineering (CRE).
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