Study Program
The course consists of Compulsory Modules and Advanced Modules in Language Technologies and Computer Science, complemented by a Project, and a Master thesis, for a total of 120 ECTS credits.
The Compulsory Modules and their range of possible syllabi are as specified in table 1 below.
| Module | Topics | Credits | |
| Language Technologies (24 ECTS minimum) | Foundational (LT-M1) |
Statistical methods, symbolic methods, cognition, corpus, text and speech, foundations of Linguistics | at least 6 |
| Computational Syntax and Morphology (LT-M2) |
Finite state techniques, probabilistic approaches, formal grammars, tagging, chunking, parsing | at least 9 | |
| Computational Semantics, Pragmatics and Discourse (LT-M3) | Syntax-semantics interface, semantic construction, dialogue, ontologies, formal semantics | at least 9 | |
| Computer Science (24 ECTS minimum) | Data Structures, Data Organization and Processing (CS-M1) | Algebraic data-types, relational databases, semi-structured data and XML, information retrieval, digital libraries | at least 6 |
| Logic, Computability and Complexity (CS-M2) | Logic and inference, automata theory, computability theory, complexity theory, discrete mathematics | at least 9 | |
| Formal Languages and Algorithms (CS-M3) | Formal grammars and languages hierarchy, parsing and compiler design, search techniques and constraint resolution, automated learning | at least 9 |
The Advanced Modules consist of 42 ECTS credits, of these at least 4 credits should be in LT and 4 in CS. These modules are based on the specific strengths in research and teaching of the partner institutions and thus vary from partner to partner. The main topics are listed in Table 2 below. From the 42 ECTS credits of this category of modules, 15 may be devoted to a project. The research masters thesis consists of 30 ECTS credit points.
| Module | Topics | Credits | |
| Language Technologies | Advanced (LT-M4) |
Machine translation, information and knowledge representation, information retrieval, question answering, speech recognition and generation, models of human language processing and understanding, psycholinguistics | at least 4 |
| Computer Science | Advanced (CS-M4) |
Artificial intelligence, knowledge representation, automated reasoning, semantic web, intelligent and multi-modal interfaces, cognitive modelling, computational psychology, neural networks, machine learning | at least 4 |
Students within the double degree program have to study at two institutions of the consortium. As such, they are jointly monitored by two lecturers (tutors), one from each institution. Each student has to develop a study plan with her/his tutors. This plan must be submitted for approval to the Joint Committee of the Consortium. The students have to complete successfully all the written and/or oral exams of the modules selected in the aforementioned study plan. The students have to submit and defend their masters thesis at either or both of their selected institutions. The masters thesis can be jointly supervised. It is defended in front of a jury with members from the two selected universities.
For more information see Modules