🎓Program Structure
Overview of the 3-year AI bachelor curriculum at VU Amsterdam.
3 years, 2 semesters per year, 3 periods per semester. Each period is about 8 weeks of classes + an exam week.
Year 1 — Foundations
| Period | Course | EC | What it covers |
|---|---|---|---|
| 1 | Computational Thinking | 3 | Solution strategies, search/sorting/graph algorithms, intro to problem-solving |
| 1 | Introduction to Artificial Intelligence | 3 | AI concepts, history, main subfields like ML and knowledge representation |
| 1 | Introduction to Psychology and its Methods | 6 | Cognition, perception, and research methods relevant to human-centred AI |
| 1 | English Language Test | 0 | Mandatory English proficiency check |
| 2 | Intelligent Systems | 6 | Knowledge representation, reasoning, search algorithms, agent architectures |
| 2 | Introduction to Python Programming for AI | 6 | Python basics: variables, control flow, data structures, libraries |
| 3 | Project Intelligent Systems | 6 | Group project — build and evaluate game-playing bots for Schnapsen |
| 4 | Logic and Sets for AI | 6 | Propositional logic, predicate logic, set theory, formal reasoning |
| 4 | Modelling Human Behaviour (SAC track) | 6 | Agent-based, cognitive, and collective behaviour models for human-centred systems |
| 5 | Academic Writing (BETA) | 3 | Formal writing, structuring arguments, citing sources, literature reviews |
| 5 | History of AI | 3 | Key milestones in computing and AI, paradigm shifts, societal impact |
| 5 | Human-Computer Interaction for AI | 6 | Usability, interface design, human–AI interaction |
| 6 | Applied Programming for AI | 6 | Web tech (HTML/CSS/JS), Git, REST APIs, building data-driven apps |
| 6 | Information Management | 6 | Databases, data structures, information organisation |
Year 2 — Specialisation
You pick either Intelligent Systems (more technical, systems-focused) or Socially Aware Computing (more human-centred, interdisciplinary). See the Specialisation Tracks section below for a full comparison.
Shared courses (both tracks):
| Period | Course | EC | What it covers |
|---|---|---|---|
| 1 | Knowledge and Data | 6 | RDF, OWL, SPARQL, Linked Data, Knowledge Graphs |
| 2 | Linear Algebra and Calculus | 6 | Vectors, matrices, linear systems, limits, differentiation, eigenvalues |
| 2 | Multi-Agent Systems | 6 | Agent reasoning, knowledge representation, Prolog programming |
| 4 | Machine Learning | 6 | Linear models, neural networks, decision trees, gradient descent, deep learning |
| 4 | Probability and Statistics | 6 | Distributions, hypothesis testing, confidence intervals, central limit theorem |
| 5 | Text Mining for AI | 6 | NLP, text classification, sentiment analysis, entity recognition, topic modelling |
Intelligent Systems track:
| Period | Course | EC | What it covers |
|---|---|---|---|
| 1 | Data Structures and Algorithms for AI | 6 | Algorithms, data structures, complexity analysis |
| 3 | Project Conversational Agents | 6 | Build a conversational agent using DialogFlow and ontology |
| 5 | Databases | 6 | ER diagrams, SQL, schema design, normalisation, concurrency |
| 6 | Project Collective Intelligence | 6 | Swarm dynamics, agent-based simulation, collective behaviour modelling |
| 6 | The Law of Artificial Intelligence | 6 | EU AI Act, legal compliance, designing lawful AI systems |
Socially Aware Computing track:
| Period | Course | EC | What it covers |
|---|---|---|---|
| 1 | Robot Interaction | 6 | Human-robot interaction, social robotics, NLP, ethics |
| 3 | Project Socially Aware Computing | 6 | Agent-based simulation for societal challenges using NetLogo |
| 5 | AI and Law | 6 | AI applications in law, ethical questions in the legal domain |
| 5 | AI in Health | 6 | AI for diagnosis, treatment, monitoring — ontologies, explainable ML |
| 6 | The Law of Artificial Intelligence | 6 | EU AI Act, legal compliance, designing lawful AI systems |
Year 3 — Minor, Research & Thesis
| Period | Course | EC | What it covers |
|---|---|---|---|
| 4 | Ethical AI | 6 | Moral agency, fairness, transparency, accountability, EU AI Act |
| 4 | Automata and Complexity (IS) or Cognitive Psychology for AI (SAC) | 6 | Formal languages, Turing machines, P/NP or perception, memory, decision-making |
| 5 | Research Design for AI | 3 | Research questions, methodology, data analysis, scientific writing |
| All year | Bachelor Project Artificial Intelligence | 15 | Individual research project, thesis, and oral presentation |
| — | Free elective minor | 30 | Your choice — any VU or exchange minor |