ECTS
120 crédits
Niveau d'études visé
BAC +5 (niveau 7)
Durée
2 years
Faculté
Faculté Sociétés et Humanités
Langue des enseignements
Anglais
Présentation
The field of Natural Language Processing (NLP) has revolutionized industries by enabling advanced generative AI technologies and fostering innovations like real-time translation, intelligent assistants, and automated content creation. UPCité’s master’s program in Computational Linguistics equips students with theoretical and practical skills in NLP, preparing them for careers in industry or research through interdisciplinary training in computer science, data science, linguistics, and AI.
A full description of the courses is available here. A more detailed description of the “parcours” and its requirements can be found here.
This master's program is part of Université Paris Cité's Graduate Schools "Artificial Intelligence and Data Science" and "Linguistics", linking master's and doctoral courses with cutting-edge research laboratories.
- The Graduate School "Artificial Intelligence and Data Science" trains specialists in artificial Intelligence and data Science, with an emphasis on interdisciplinarity Find out more >
- The Paris Graduate School in Linguistics takes a multidisciplinary approach to the study of language, covering theoretical, computational, historical, sociolinguistic and psycholinguistic linguistics. Find out more >
Objectifs
The program aims to provide students with a comprehensive mastery of generative AI methods, both from theoretical and practical perspectives. It focuses on equipping students with the skills to design, train, and deploy state-of-the-art generative models, particularly for text-related applications such as chatbots, automatic summarization, and translation. Additionally, the training emphasizes expertise in data science, with a specialization in textual data: Students will learn to analyze, process, and interpret large-scale text datasets using advanced machine learning and deep learning techniques.
This program opens doors to various career paths in both industry and research. Graduates will be well-prepared for roles such as data scientist, AI engineer, or NLP specialist in industries that leverage natural language processing technologies. Furthermore, the program provides a solid foundation for pursuing research opportunities, whether in academic institutions or applied research labs, fostering innovation in the rapidly evolving field of natural language processing.
Compétences visées
- master theory and practise of language models (including generative AIs)
- know current natural language processing and machine learning algorithms, and know how to implement them in practice to solve a given task
- be able to use major deep learning libraries
- be familiar with modern linguistic concepts for describing a variety of languages
- know how to explore and process large and varied text corpora
Ils en parlent
Armand Garrigou (class of 2024)
The Master in Computational Linguistics at Université Paris Cité gave me all the knowledge I needed to deal with Natural Language Processing tasks, in both professional and academic contexts. The theoretical teaching is highly relevant: basics of Machine Learning, Formal Languages, Deep learning, Language models and specificities of NLP tasks. The courses are complemented by various projects (Sentiment Analysis, POS tagging, Automatic Speech Recognition, Text Generation, Automatic translation, etc.) of varying lengths (from one week to the whole semester). This complementary nature of theoretical teaching and projects ensures excellent learning outcomes. The diversity of linguistics courses enables students to discover all aspects of linguistics and to specialize in a particular component at the end of the Master's degree.
The teachers are passionate about their subjects and experts in their fields. The courses are taught in English, which is a real plus. The courses are constantly updated to keep up with technological innovations and to stay relevant in the fast-changing field of NLP.
I can only recommend the L3 preparatory program for the Master's, as it enabled me to acquire the fundamentals of everything taught during the Master's, to feel more at ease with complex topics and to integrate easily into this new path when I reoriented.
Isaac Murphy (class of 2023)
I started the computational linguistics masters program at UPCité with a degree in Linguistics and very little experience in anything computational. Over the two year program, not only did I learn how to apply computational methods to linguistic research but also how to confidently write code for machine learning and data processing using standard industry libraries. Most importantly, we learned the basic theories behind all language models and how best to approach their strengths and weaknesses.
Although there is plenty of work in the courses, the skills you learn are certainly worth it. I am currently working as an NLP data scientist at a company in the US that is working to design tools to better support psychiatrists and and other mental health workers
Haoxian Wang (promo 2018)
Le master de linguistique informatique de Paris Diderot est une formation qui répond bien aux besoins de l’industrie du domaine TAL. Avant de faire ce master, j’ai fait une formation linguistique en Chine, et ai suivi par moi-même des tutoriels de programmation et de maths. Le parcours LI m'a permis de rapidement me former en informatique et de m’améliorer en linguistique, avec une combinaison des deux pertinente pour les besoins réels des entreprises. Ce parcours reste toujours à jour sur l’état de l’art du domaine, je suis capable de suivre le développement du domaine après avoir été diplômé grâce à cette agilité que j’ai apprise de mes professeur(e)s. Les nombreux TPs que nous avons faits en équipe étaient bien conçus, et permettent de maîtriser les algorithmes de TAL, améliorer le niveau de programmation. Le mode de travail en équipe est utile dans mon travail actuel. Grâce à LI, je suis devenu un ingénieur en TAL et j’aime beaucoup ce métier.
Chuyuan Li (promo 2019)
I studied French language and literature in China and had a master of business and management. With little background in computational linguistics, I came into this program with a lot of luck. Then when I actually stepped into this world, luck vanished, all that was left was work, hard work.
I found myself surrounded by linguistic theories, programming language trainings and algorithm logics - each of them could be a tough subject alone - yet this program asked you to manage them all. Saying all this is not meant to discourage you. But it’s important to realize that this program is tough, asking you to push your limitations again and again. Sometimes we feel lost. More often, we get support: professors, classmates they are trustworthy and incredibly kind to help you out. All you need to do is ask. Thinking backwards, I cherish these moments. They made me believing in this world: the joy of manipulating a text, the pride of succeeding in running a program, the kindness of fellows, and the feeling of fraternity. As for now, I am a PhD student working on formal and statistical modelling of dialogues at LORIA.
Johanna Simoens (promo 2018)
J'ai commencé le master de Linguistique Informatique de Paris Diderot à la suite d'une licence MIASHS (Mathématiques et Informatique Appliquées aux Sciences Humaines et Sociales) parcours Linguistique. J'ai fait le M1 à Dublin (en Erasmus) et le M2 à Paris. J'ai trouvé les cours passionnants.
Les cours de M2 aboutissent généralement à des projets d'informatique, ce qui complète bien la formation sur le plan pratique. Ils permettent de se confronter à des problèmes techniques concrets et d'acquérir une rigueur méthodologique nécessaire dans le milieu de la recherche comme en industrie. Les projets d'informatique sont aussi un bon moyen de stimuler une entraide entre les étudiants (issus de domaines différents: linguistique, Langues étrangères, Informatique, Mathématiques, etc) ont chacun des connaissances à apporter aux autres. La taille réduite de la promotion 2018 facilitait également cette entraide entre étudiants. Les professeurs étaient disponibles et désireux d'améliorer leurs cours par la prise en compte du ressenti des étudiants.
Programme
The Master's program spans two years, divided into four semesters, with each semester corresponding to 30 ECTS credits. The first three semesters consist of on-site courses taught in English, offering a well-rounded curriculum organized into three main categories:
Natural Language Processing Lectures (≥ 45 ECTS)
These courses provide both theoretical foundations and practical insights into the tools and algorithms central to modern NLP systems.
Linguistics Lectures (≤ 18 ECTS)
Shared with the Master’s in Linguistics, these courses ensure students grasp the theoretical challenges encountered when working with real-world textual or speech data.
Computer Science and Data Science Lectures (≥ 27 ECTS)
Focused on equipping students with the skills to design and implement NLP algorithms, these hands-on courses emphasize programming, data processing, and large-scale text corpus analysis, ensuring readiness for practical applications.
Find out more: Master's degree structure and course descriptions
Stages et projets tutorés
On top of practical sessions in regular courses, the second semester of M1 includes a “NLP project”, where students are supervised by a lecturer to carry out a NLP full program in pairs.
M1 includes an internship (minimum 1 month, average duration 2 to 3 months), either within a NLP company or in a research laboratory.
The second semester of M2 is entirely devoted to an internship, likewise in a NLP company or research laboratory.
Contrôle des connaissances
Most courses are assessed by a final exam and/or continuous assessment.. Special arrangements are possible for particular situations (dependent children, work contracts, etc.).
Aménagements particuliers
Admission
Public cible
Due to its multi-disciplinary character, candidates for this Master’s degree can have different profiles: we welcome either students with a main training in linguistics but with knowledge and interest in computer science and mathematics, or students trained in computer science but interested in linguistics and the formal organisation of languages.
Note that while it is possible to enter the Master’s programme with little to no knowledge of linguistics but some knowledge in computer science and in mathematics is required.
A detailed description of the prerequisites is available at https://u-paris.fr/linguistique/futurs-etudiants/conditions-acces-li/
Conditions d'admission
A Bac+3 is required for admission, which is determined by a pedagogical commission upon review of the application dossier.
For more details on admission requirements and prerequisites, visit https://u-paris.fr/linguistique/futurs-etudiants/conditions-acces-li/
Pré-requis
- See admission requirements and prerequisites: https://u-paris.fr/linguistique/futurs-etudiants/conditions-acces-li/
- Ability to read scientific texts in English and understand English lectures.
Modalités de candidature
Droits de scolarité
National tuition fees are set annually by the “Ministère de l'Enseignement Supérieur et de la Recherche”. Mandatory and optional contributions are added according to the student's individual situation.
Et après ?
Poursuites d'études
Doctoral studies, for students who have completed an M2 research internship, and depending on the results obtained.
Insertion professionnelle
Taux insertion professionnelle 90%
*Enquête du MESRI sur les diplômés 2019, 30 mois après obtention du diplôme.
Effectif des diplômés |
Effectif des répondants |
Taux de réponse |
Part des diplômés en formation initiale |
Part des diplômés en formation apprentissage |
Part des diplômés en formation continue |
17 |
11 |
65% |
91% |
- |
9% |
Part des cadres et des professions intermédiaires |
Part des emplois stables |
Part des emplois à plein temps |
Part des emplois en adéquation avec le niveau d'études |
Part des emplois en adéquation avec la formation suivie |
100% |
67% |
100% |
- |
100% |
Débouchés professionnels
À l'issue du master, l'orientation professionnelle ouvre sur des postes de linguiste informaticien.ne et ingénieur.e en sciences de données textuelles dans des entreprises d'intelligence artificielle orientées vers le traitement du texte écrit.
L'orientation recherche peut permettre de poursuivre en doctorat de linguistique informatique.
Référentiel
Référentiel ROME
- Communication
- Conception de contenus multimédias
- Conseil en formation
- Coordination pédagogique
- Coordination d'édition
- Enseignement supérieur
- Enseignement général du second degré
- Enseignement des écoles
- Formation professionnelle
- Réalisation de contenus multimédias
- Orthophonie
Référentiel RNCP
38696
Contacts
Dernière mise à jour le 30 janvier 2025