Program Overview

Artificial Intelligence Master Programme

The Artificial Intelligence (AI) Master programme is oriented towards Hybrid intelligence, where AI systems and humans collaborate. The AI master programme has a human-centric approach to AI. It is aimed at providing students with solid underpinnings in the technical and algorithmic aspects of AI, combined with a thorough understanding of human functioning from human-oriented sciences.

Programme Description

Students approach the study of AI both from a technical perspective, focusing on the understanding, analysis and development of novel AI algorithms, and from a societal and human perspective, looking into questions such as “how can we develop and evaluate computer-based technology that exploits knowledge about human functioning?” and “how can human and AI-technology complement each other and collaborate with each other?”

Programme Structure

The first year includes courses that focus on core AI topics, while the second year is devoted to the track “Cognitive Science”, “AI for Health" or a coherent set of electives.

Career Opportunities

Graduates from the Master in Artificial Intelligence typically move on to pursue a career as a.o. Data Scientists, Machine Learning Engineers, or AI specialist at leading ICT companies.

Programme Details

• Level: Master
• Language: English
• Duration: 2 years
• Type: Full Time
• Credits: 120 EC
• Faculty: Faculty of Science

Compulsory Courses

These courses are obligatory for all AI master tracks.

• Evolutionary Computing (P1, 6 EC)
• Knowledge Representation (P2, 6 EC)
• Multi-Agent Systems (P2, 6 EC)
• Socially Intelligent Robotics (P2, 6 EC)
• AI and Society (P3, 6 EC)
• Experimental Design and Data Analysis for AI (P4, 6 EC)
• Natural Language Processing (P5, 6 EC)

Electives

• Bioinformatics
  • Fundamentals of Bioinformatics (P1, 6 EC)
  • Algorithms in Sequence Analysis (P2, 6 EC)
  • Structural Bioinformatics (P4, 6 EC)
  • Bioinformatics for Translational Medicine (P5, 6 EC)
• Deepening AI
  • Mini-Master Project AI (Ac. Year, 6 EC)
  • Advanced Machine Learning (P1, 6 EC)
  • Intelligent Interactive Systems (P1, 6 EC)
  • Knowledge Organization (P1, 6 EC)
  • Behaviour Dynamics in Social Networks (P2, 6 EC)
  • Deep Learning (P2, 6 EC)
  • Dynamic Programming and Reinforcement Learning (P2, 6 EC)
  • Machine Learning and Reasoning for Health (P2, 6 EC)
  • The Social Web (P2, 6 EC)
  • Machine Learning for Graphs (P3, 6 EC)
  • Project Reinforcement Learning (P3, 6 EC)
  • Learning Machines (P3, P6, 6 EC)
  • Advanced Logic (P4, 6 EC)
  • Entrepreneurship in Analytics and AI (P4, 6 EC)
  • Knowledge Representation on the Web (P4, 6 EC)
  • Applications of Modal Logic for AI (P5, 6 EC)
  • Data Mining Techniques (P5, 6 EC)
  • Machine Learning for the Quantified Self (P6, 6 EC)
• Health Sciences
  • Health Psychology (P1, 6 EC)
  • Health Promotion and Disease Prevention (P2, 6 EC)
  • Prevention of Mental Health Problems (P3, 6 EC)
• Cognitive Science
  • Seminar Cognitive Neurosciences (P1, 6 EC)
  • Aging and age-related disorders (P2, 6 EC)
  • Behaviour Dynamics in Social Networks (P2, 6 EC)
  • Neural Models of Cognitive Processes for AI (P2, 6 EC)
  • Brain Imaging (P4, 6 EC)
• Other Electives
  • Web Data Processing Systems (P2, 6 EC)
  • History of Digital Cultures (P3, 6 EC)
  • ICT4D: Information and Communication Technology for Development (P5, 6 EC)
  • ICT4D in the Field (P6, 6 EC)
• Social Robotics
  • Essentials of Media Psychology (P1, 6 EC)
  • Communicative Robots (P2, 6 EC)
  • Socially Intelligent Robotics Project (P3, 6 EC)
  • Social Robotics (P4, 6 EC)
• Language Technology
  • Programming in Python for Text Analysis (P1, 6 EC)
  • Subjectivity Mining (P1, 6 EC)
  • Communicative Robots (P2, 6 EC)
  • Language as Data (P2, 6 EC)
  • Machine Learning for NLP (P2, 6 EC)
  • Applied Text Mining 1: Methods (P3, 6 EC)
  • Advanced NLP (P4, 6 EC)

Research Project

• Master Project AI (Ac. Year, 30 EC)

Tracks

Artificial Intelligence for Health

• AI for Medical Imaging (P1, 6 EC)
• Medical AI (P1, 6 EC)
• Machine Learning and Reasoning for Health (P2, 6 EC)
• Medical Informatics Basics (P5+6, 6 EC)

Cognitive Science

• Seminar Cognitive Neurosciences (P1, 6 EC)
• Neural Models of Cognitive Processes for AI (P2, 6 EC)
• Brain Imaging (P4, 6 EC)
• Master Thesis: Research Project Cognitive Science (Ac. Year, 30 EC)