2nd year MSc
in Natural Language Processing

CAMPUS
PLG
LANGUAGE
ANGLAIS
CLASSROOM
ECTS CREDITS
60

Goals of the 2nd year MSc in NLP

The 2nd year MSc in NLP offers specific courses applied to NLP such as neural networks, statistics, algorithms... The fourth semester is devoted to the master thesis.

Presentation of the 2nd year MSc in NLP

During the 2nd year MSc in NLP, you will follow courses on logic, statistics, linguistics, programming for NLP, as well as more advanced courses in NLP.

The second semester consists of a paid internship. This personal project can be carried out either in one the research centers associated with the MSc degree (ATILF or LORIA) or in the private sector.

In both cases, the project is supervised by a senior member of staff (a University lecturer or a researcher). The research project requires an original solution to a problem situated within an existing scientific domain.

About Erasmus Mundus

Our MSc degree in NLP is a part of the Erasmus Mundus consortium « Language and Communication Technologies (LCT) », which speaks to the international recognition of the quality training our program offers, as well as the multicultural environment it provides.

NLP Degree outline

And after the 2nd year MSc in NLP?

You will reach very quickly the professional life worldwide. Continuation for Ph.D. and/or research is possible.

MSc in NLP CONTACT

Miguel COUCEIRO

Responsible for the 2nd year MSc in NLP

Karine WEISSE

Administrative Contact

2nd year MSc in NLP course description (click on the title to access the course description)

Semester 9
DEEP LEARNING AND DATA MINING

The objective of this course unit is to acquire machine learning tools, mainly deep neural networks and factorisation matrices, to be able to manipulate these tools when considering practical applications (tweets, traces of e-learning), as well as to expand the students’ knowledge in semantic web and the extensions of analysis of formal concepts for textual and relational data processing.

TEXT AND SPEECH PROCESSING

Automatic processing of texts and of speech involves different methods of machine learning. This class will introduce these methods and illustrate their use through examples and practical application using tools developed for text and speech processing.

NATURAL LANGUAGE PROCESSING AND DISCOURSES

This course unit gathers courses which deal with discursive and semantic processing of language

LEXICON AND GRAMMARS FOR NLP

This course unit introduces advanced tools for the computational modeling of different types of linguistic information which describe lexical units (lexical resources) or the rules of organisation of larger units (grammar)

PROJECTS AND FOREIGN LANGUAGE
Semester 10
PAID INTERNSHIP
  • Paid internship in company or research laboratory

Chercheur à la JuangXi Academy of Sciences en Chine : linguistique computationnelle et modélisation formelle de la langue naturelle.

Sai Q.Chercheur

Post-Doctorante à l'Université de Fribourg en Suisse : perception et contrôle des mouvements chez les êtres humains.

Amandine D.Post-Doctorante

Doctorant à LUTIN à Paris : thèse sur la mesure par oculométrie et le motion tracking (enregistrement de mouvement).

Jean-Luc P.Doctorant