🔀Specialisation Tracks
Comparing the Intelligent Systems and Socially Aware Computing tracks.
In Year 2 you choose one of two specialisation tracks. Your choice determines roughly 30 EC of your curriculum and appears on your graduation document. You can mix courses from both tracks, but if you do, no track label will appear on your diploma.
Intelligent Systems (IS)
The IS track is more technical and systems-focused. It gives you a stronger foundation in algorithms, databases, and building intelligent software systems.
Track-specific courses:
| Course | Year | EC | Focus |
|---|---|---|---|
| Data Structures and Algorithms for AI | 2 | 6 | Core CS algorithms, complexity, data structures |
| Databases | 2 | 6 | SQL, relational databases, data modelling |
| Project Conversational Agents | 2 | 6 | Building dialogue systems and chatbots |
| Project Collective Intelligence / The Law of AI (choose 1) | 2 | 6 | Agent simulation or AI law |
| Automata and Complexity / Computational Intelligence (choose 1) | 3 | 6 | Formal languages or optimisation algorithms |
Pros: Stronger technical/CS foundation. Keeps more master's options open (especially CS masters). Better preparation for software engineering roles. Covers DSA which is essential for technical interviews.
Cons: Less exposure to human-centred AI, ethics, and social impact. Heavier on math and programming.
Socially Aware Computing (SAC)
The SAC track is more human-centred and interdisciplinary. It focuses on how AI interacts with people and society, covering robotics, psychology, law, and health.
Track-specific courses:
| Course | Year | EC | Focus |
|---|---|---|---|
| Robot Interaction | 2 | 6 | Human-robot interaction, social robotics |
| Project Socially Aware Computing | 2 | 6 | Building socially aware AI systems |
| The Law of Artificial Intelligence | 2 | 6 | EU AI Act, legal compliance |
| AI and Law / AI in Health (choose 1) | 2 | 6 | Legal AI or healthcare AI |
| Cognitive Psychology for AI | 3 | 6 | Perception, memory, attention, decision-making |
Pros: Broader interdisciplinary perspective. Great for UX/HCI, policy, healthcare AI, or ethics-focused careers. Unique courses not found in most CS programs.
Cons: Fewer core CS courses (no DSA, no Databases). May need bridging courses for technical master's programs. Less preparation for algorithm-heavy roles.
Shared courses (both tracks)
Knowledge and Data, Linear Algebra and Calculus, Multi-Agent Systems, Machine Learning, Probability and Statistics, Text Mining for AI, Ethical AI, Research Design for AI, and the Bachelor Project.
Tip: If you're unsure which track to choose, the IS track keeps more doors open for technical master's programs. But if you're drawn to human-centred AI, psychology, or ethics, SAC is genuinely unique and valuable.