MA 45: Double Major
First Semester
The lecture provides advanced knowledge of deep learning techniques such as FCN, CNN and LSTMs, practical application examples for NN architectures, e.g. in the field of image and speech processing. Current models and methods of machine learning and their technical background are presented. Building on this, models from the field of deep learning, such as CNNs, RNNs and sequence-to-sequence architectures, are discussed. The theoretical foundations of these models, such as training through backpropagation, are also discussed in detail. For all the models covered, it is shown how they are used in practice for specific problems such as image processing and text generation.
- Lecture: Deep Learning (Katharina Breininger), see WueStudy
- Exercise (Katharina Breininger), see WueStudy
- Tutorium (Christof Weiß)
Introduction to Computational Literary Studies (Fotis Jannidis)
Second Semester
Lecture with Exercise and Tutorium.
Courses in WueStudy include:
Multilingual Natural Language Processing (Goran Glavaš)
Machine Learning for Natural Language Processing (Andreas Hotho)
Computational Audio and Music Analysis (Christof Weiß)
Third Semester
You’ll apply what you have learned until now by performing a research project of your own.
additionally, choose 5 ECTS from the electives listed below.
Fourth Semester
In the 4th semester, you should write your master’s thesis and finally present it in the colloquium.
With a double major, you are free to decide in which of your majors you would like to write your thesis (or whether you find a subject that fits both subjects).
Mandatory Electives
Music Information Retrieval (Christof Weiß) (Exercise)
There will be additional offers in the future, e.g., from the area of Computer Vision.
If you are studying the single major (120 ECTS) and visit two of the alternatives, the second course can be accounted for as mandatory elective.
You’ll apply what you have learned until now by performing a research project of your own.
TODO
