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.
|Language Technologies (24 ECTS minimum), at least 4 in specialized modules.||Methodologies
|Statistical methods, symbolic methods, cognition, corpus, text and speech, foundations of Linguistics||at least 3|
|Finite state techniques, probabilistic approaches, formal grammars, tagging, chunking, parsing||at least 6|
|Computational Semantics, Pragmatics and Discourse (LT-M3)||Syntax-semantics interface, semantic construction, dialogue, ontologies, formal semantics||at least 6|
|Computer Science (24 ECTS minimum), at least 4 in specialized modules.||Data Structures, Data Organization and Processing (CS-M1)||Algebraic data-types, relational databases, semi-structured data and XML, information retrieval, digital libraries||at least 3|
|Logic, Computability and Complexity (CS-M2)||Logic and inference, automata theory, computability theory, complexity theory, discrete mathematics||at least 6|
|Formal Languages and Algorithms (CS-M3)||Formal grammars and languages hierarchy, parsing and compiler design, search techniques and constraint resolution, automated learning||at least 6|
Table 1: Core Modules
There are the following specialized LT and CS modules with the respective minimum ECTS credit requirements and examples of included topics (non-exhaustive list). The research masters thesis consists of 30 ECTS credit points.
|Language Technology||(LT-M4)||Machine translation, information retrieval, question answering, speech recognition and generation, models of human language processing and understanding, psycholinguistics, multimodality, Language Resources, Computational Semantics, Formal Semantics, Inference in NLP.||at least 4|
|Computer Science||(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|
Table 2: Specialized Modules
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 thesis is supervised by at least two supervisors, one from each host institution. The thesis is submitted at and should satisfy the regulations of both hosting institutions, and is assessed at both institutions.
The key point to ensure is that you have covered the required topics and gained sufficient ECTS credits. Within these constraints there is a lot of flexibility. The program ensures that all students receive a common education that covers the core topics in LCT, but their specific scientific profile is shaped by the pair of Universities they choose for the first and second year of their studies.
At each partner university, local grade scale are used. When courses are recognized at the other partner, grades are converted according to the table below. This takes in to account the requirements on grade distribution set by the ECTS scheme.
|UBC||0-4.9||5-6.9||7-8.9||9-10||10 with dist.|
UL: University of Lorraine
CUNI: Charles University
RUG: University of Groningen
UBC: University of the Basque Country
USAAR: Saarland University
UM: University of Malta
UT: University of Trento