Elective courses
Table of contents
Didactics of Media
ECTS: 5
[WT3: Didactics of Media]
Students learn the theoretical foundations of media didactics. They will be able to formulate learning objectives, know how to achieve them with the help of media as well as how to carry out suitable forms of learning success control. Students will have acquired the ability to evaluate existing e-learning offerings.
Seminar
ECTS: 5
[M11 Seminar (PS)]
This course is designed to explore the applications of deep learning algorithms in finance, leveraging large datasets and computational power. The course provides hands-on experience by implementing state-of-the-art deep learning algorithms to solve complex financial problems. The grade for the course is based on three assignements: paper, code submission in R or Python, and a presentation. Key topics include various neural network models like Feedforward, Bayesian, Recurrent, GANs, LSTM, CNN, and techniques in reinforcement learning, applied to areas such as financial trading, portfolio analysis, and risk management.
Data Mining
ECTS: 5
[W2-DM: Data Mining]
The students gain knowledge in basic methods, techniques and algorithms for data mining. They learn how to extract knowledge from raw data. They know how to apply data mining tools and understand data mining models.
Contents include:
- data mining processes, data sources
- Data Wrangling, Data Pre-Processing, Feature Engineering
- Data models: regression, classification, clustering, association
- techniques: linear and logistic regression, decision and regression trees, random forest, boosted trees, SVN
- k-NN, k-Means, Agglomerative Clustering, Frequent Item Sets, PCA
- Evaluation and cross-validation, choice of best model,
- boosting and regularization
- programming in R with RStudio and Python.
Statistical Learning in Finance and Insurance
ECTS: 4
[Statistical Learning in Finance and Insurance]
Introduction to statistical learning methods for use in finance and insurance.
Interdisciplinary Additional Courses ("AWE")
ECTS: 2
Every Semester students are able to choose 1-2 AWE from a great range of general courses in order to complement their regular curriculum courses. You will be able to see the full range of optional courses during the course registration period. As not all topics are published yet at the time of the application, please simply select "AWE - General Course" on the learning agreement and then apply for your specific General Course(s) before the semester starts. Please note that "AWE" have limited places, acceptance is not guaranteed.
Current list of AWE for the summer semester 2026:
- AWE: Gender and Computing
- AWE: Modern Mythology: Technology and Cultural Business Design
- AWE: The economic of world peace
- AWE: 3D and 4D Printing with Sustainable Materials
German as a Foreign Language
ECTS: 4
Our language department offers a wide range of courses - from General German classes, focusing on the basics of grammar and conversation, to more advanced German courses with specializations in the fields of Design, Business and Technology. Based on your German level you have already got you can attend a German as a Foreign Language course. Please put the level already on your Learning Agreement, e.g. "German as a Foreign Language, Level A.2".