These categories drive the specialization/profile circle in the dashboard.
They are intentionally different from the regulation rule groups such as INFO-THEO or ML-CS.
Rule groups answer where a course counts in the degree.
Visualization categories answer which academic profile a course strengthens.
| Code | Label | Reference ECTS | Purpose |
|---|---|---|---|
SOFTWARE_ENG |
Software Engineering | 12 | architecture, software quality, programming languages, software practice |
THEORY |
Theory | 18 | algorithms, formal methods, cryptography, complexity |
MATHEMATICS |
Mathematics | 18 | linear algebra, statistics, mathematical ML foundations |
SYSTEMS_SECURITY |
Systems & Security | 12 | operating systems, networks, infrastructure, security |
DATA_DATABASES |
Data & Databases | 12 | database systems, data engineering, data-intensive computing |
AI_ML |
AI & Machine Learning | 18 | machine learning, neural networks, NLP, data-driven AI |
VISION |
Vision | 12 | computer vision, computational photography, visual perception |
HCI_UX |
HCI & UX | 12 | interaction techniques, human-computer interaction, usability |
ROBOTICS |
Robotics | 12 | robotics, autonomous systems, embodied AI |
INTERDISCIPLINARY |
Interdisciplinary | 12 | courses that connect Informatics with other domains |
reference_ectsis a visualization cap, not a formal degree requirement.- A course may contribute to multiple visualization categories.
- Regulation rule groups still stay authoritative for official degree assignment.
- The profile circle should emphasize strengths, not enforce hard graduation rules.
The first seed uses a hybrid approach:
- prefer Informatics-relevant courses already present in D1
- attach them to one or more visualization categories
- keep the mapping table open for later regulation-specific overrides
That gives the dashboard a stable specialization view without replacing the formal examination-regulation logic.