MSc Advanced Data Science
The Advanced Data Science track provides a deeper insight into the general application and technical details of data management along with analysis algorithms and techniques. The modules in this track require profound mathematical and computing knowledge. It allows students with a strong mathematical and computing background to dive deeper into questions on data mining, data analytics, and machine learning.
Semester 1
| Subjects | Type | ECTS | Syllabus |
|---|---|---|---|
| Digital Societies and Future Economies | Mandatory | 6 | — |
| Data Science Concepts | Mandatory | 5 | — |
| Data Science Tools | Mandatory | 4 | — |
| Current Topics and Applications in Data Science | Mandatory | 5 | — |
| Communication and Presentation Skills | Mandatory | 4 | — |
| IT Law and Ethics | Mandatory | 6 | — |
Semester 2
| Subjects | Type | ECTS | Syllabus |
|---|---|---|---|
| Digital Public Spheres | Mandatory | 5 | — |
| Digital Business Functions and Models | Mandatory | 6 | — |
| Text Analysis and Natural Language Processing | Mandatory | 5 | — |
| Data Science Lab | Mandatory | 4 | — |
| Artifical Intelligence in Business and Society | Mandatory | 5 | — |
| Digital Transformation and Innovation | Mandatory | 5 | — |
Semester 3
| Subjects | Type | ECTS | Syllabus |
|---|---|---|---|
| Data Analytics | Mandatory | 5 | — |
| Data Mining | Mandatory | 5 | — |
| Machine Learning | Mandatory | 6 | — |
| Data Management with Python | Mandatory | 6 | — |
| Elective from other concentrations | Mandatory | 4 | — |
| Elective from other concentrations | Mandatory | 4 | — |
Semester 4
| Subjects | Type | ECTS | Syllabus |
|---|---|---|---|
| Thesis | Mandatory | 30 | — |