AI & Robotics (MSc)

Overview

This English-taught MSc programme prepares you to meet growing global demand for experts in artificial intelligence and robotics. It combines theoretical foundations with hands-on learning through a modern learning design, giving you a deep understanding of algorithms, system architectures and practical applications in both fields. You will learn how to design, implement and evaluate complex robotic systems and AI methods across real-world settings.

The curriculum emphasizes science-based methods so you can collect, analyse and interpret data relevant to intelligent systems. Practical assignments and projects are used alongside theory to develop the technical skills needed to build and test AI and robotics solutions. The programme also supports creating novel approaches to emerging technological challenges.

Graduates are prepared for careers across industries such as manufacturing, healthcare, transportation and entertainment, and are equipped to continue into research or academic roles. The course stresses teamwork, lifelong learning, and professional development, while encouraging reflection on sustainability, democratic citizenship and the social and ethical implications of technology.

Key outcomes — what you will be able to do by graduation:

• Apply theory-grounded, science-based methods to design and develop innovative, effective and sustainable AI and robotics technologies
• Collect, analyse and evaluate data for building and assessing AI and robotics systems
• Devise novel technical solutions to current and future challenges in AI and robotics
• Work productively in diverse teams and pursue continuous professional and technical development
• Recognise and reflect on the social, ethical and sustainability dimensions of your research and technology applications

Our teaching model combines research-led content with active, reflective learning rather than rote memorisation. Throughout each semester students complete learning-oriented assignments and receive personalised feedback from faculty, enabling continuous progress monitoring and deeper understanding. The programme is delivered as a modularised Master’s degree that blends theoretical foundations with hands-on practice, preparing you to design and implement intelligent systems and mobile robots.

Coursework covers core AI topics—problem solving, decision making, and knowledge representation—alongside robotics-specific material such as algorithms for autonomous navigation. You will study neural networks and their training algorithms, optimisation methods, and applications in computer vision and natural language processing. Complementary modules address data analysis, statistical techniques, data visualisation and data mining. Practical assignments and project work are embedded throughout to develop coding, experimentation and system-integration skills. The programme culminates in the interdisciplinary Learning in Transformation Project, a scientific research project focused on real-world problems and practical, research-based solutions.

Key modules (examples)

• Problem solving, decision making and knowledge representation in AI
• Algorithms for autonomous robot navigation and control
• Neural networks, training algorithms and optimisation techniques
• Computer vision and natural language processing applications
• Data analysis, statistical methods and data visualisation
• Data mining and applied machine learning
• Interdisciplinary research project: Learning in Transformation Project

Learning outcomes

• Apply formal methods for representing knowledge and designing decision-making agents
• Design and implement algorithms for autonomous robot navigation and perception
• Develop, train and optimise neural network models for vision and language tasks
• Analyse and visualise data using statistical and data-mining techniques to support AI solutions
• Integrate theoretical knowledge with practical system development through project-based work
• Conduct interdisciplinary, research-oriented projects addressing real-world problems

Programme requirements & commitments

• Full-time enrolment required
• Expect to plan for approximately 40 hours of work per week
• Active participation in continuous, learning-oriented assignments and practical projects
• Completion of the Learning in Transformation Project as a capstone research experience

For full module lists and detailed curriculum planning, consult the programme’s official curriculum information on the department website.

Graduates can pursue technical and development roles in industry sectors such as manufacturing, healthcare, transportation, and entertainment, working on problems like autonomous systems, perception, and intelligent automation. The programme’s strong emphasis on system design, data-driven evaluation and ethical reflection prepares students for roles as AI/robotics engineers, applied machine learning specialists, or systems developers.

For those interested in research or academia, the research-oriented projects and advanced coursework provide a solid foundation to continue with doctoral studies or applied research roles in labs and R&D departments.