Overview The programme is a two‑year (four‑semester) Master’s degree taught in English that brings together computational linguistics, machine learning, and knowledge representation and reasoning in a single interdisciplinary curriculum. Its distinctive focus is on developing intelligent computer systems while also treating formal models of human cognitive processes.
What you will learn You will gain the theoretical foundations and practical skills needed to design and implement systems that process natural language, learn from data, reason about information, and solve problems autonomously. Coursework emphasizes computational linguistics, knowledge representation and reasoning, machine learning, and statistical modelling, combining algorithmic and formal perspectives.
How it is taught The programme is jointly offered by the Department of Computer Science and the computational linguistics and psycholinguistics groups in the Department of Linguistics, giving you access to expertise and research across both disciplines. This structure supports interdisciplinary training and opportunities to engage with ongoing research in language, learning, and reasoning.
Key facts (requirements and structure)
The programme begins with core lectures introducing the fundamentals of language, learning, and reasoning. Because the degree is explicitly interdisciplinary, incoming students are expected to have varying strengths across three foundation areas — mathematics, computer science, and linguistics — and the curriculum is designed to close any gaps early on.
All students build deeper foundational knowledge through three basic modules. From there you broaden and deepen your expertise via advanced electives, two project modules, and an individual research module. As you move through the course, responsibility for formulating research questions progressively shifts from instructors to you, culminating in a larger, independent research effort: the MSc thesis.
Learning outcomes emphasize a solid grasp of the theoretical and practical foundations of language, learning, and reasoning; the ability to integrate knowledge across mathematics, computing, and linguistics; and growing independence in defining and pursuing research problems. The structure gives you flexibility to specialise through electives and projects while gaining hands-on experience in research methods before completing your thesis.
Requirements (concise)
Admission requirements
This master's program expects applicants to already have practical programming experience and solid academic background in at least one relevant foundation area. Students with degrees in computational linguistics, computer science, linguistics, or related fields such as mathematics or psychology are welcome — the program is interdisciplinary and accepts a variety of prior study profiles.
Acceptable foundation areas are:
You must provide documentation that demonstrates your prior knowledge and programming ability; acceptable forms of evidence are described below.
Requirements (bullet points)
Winter Semester (International)
Information about the application deadlines can be foundhere.
Graduates are prepared for roles that require building and evaluating intelligent language-processing systems and applying machine learning and reasoning methods. Typical career paths include positions in NLP/AI engineering, data science, research & development in industry, and roles in interdisciplinary teams that bridge linguistic insight and computational methods.
The programme also provides a strong research foundation for students who wish to pursue doctoral studies in computational linguistics, AI, cognitive modelling or related fields.
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