Computational linguistics and AI
Track directors: François Yvon (CNRS / Sorbonne Université) et Benoît Crabbé (Université Paris Cité)
Capacity: 10
General organization
The master’s student must register to one of the tracks. These tracks ensure the acquisition of genuine expertise in the concepts, methods, and techniques specific to each discipline, enhancing the clarity of skills associated with the diploma. The program establishes a common cultural foundation from the first year (M1) through a core curriculum and introductory courses to the different disciplines. In the second year (M2), the majority of courses are fully interdisciplinary and open to students from all tracks. Our goal is to cultivate cognitivists equipped with both robust disciplinary expertise and a broad interdisciplinary culture, essential elements for fostering meaningful collaboration across disciplines.
During the M2, all students will do a long internship during the 2nd semester. During the 1st semester, they will prepare for the internship. Spending one day in the lab (or a parent lab in the case of an internship outside Paris), they will work on the bibliography and clarify the research research question and forseen methods and statistical tests. At the end of 1st semester of M2, students will submit a preregistration document to their track directors, and present for 8 min in front of a jury at the end of January. This is crucial to learn more about the reproducibility crisis, and good practices to overcome it. At the end of the 2nd semester, students will submit a full report and present in front of an interdisciplinary jury the work they did during their internship.
Specific to this track
The Computational Linguistics and Artificial Intelligence track provides comprehensive training in the models and methods of natural language processing, from the linguistic and mathematical foundations of deep neural networks to the applications of large language models for information access, dialog systems, and machine translation. Its position within the cog-SUP Master’s program in Cognitive Sciences, offers a unique gateway to computational psycholinguistics and neurolinguistics, allowing exploration of the interfaces between language, perception, memory and action, with applications in robotics and human-machine interaction. At the end of their training, students will have a thorough understanding of the concepts, methods and techniques of natural language processing and artificial intelligence, and their implementation in advanced language information processing systems.
The courses on offer cover a wide range of topics, from linguistic modeling in phonology, syntax and semantics, to the algorithmic foundations of language processing, speech processing and deep learning – in the first year; the second year offers more in-depth studies in psycholinguistics and computational field linguistics on the one hand, and in more applied fields such as machine translation, text mining, dialogue systems and information retrieval on the other hand. Students can also choose elective courses offered in other Masters programs offered by partner universities, to further enrich and/or specify their knowledge.
The Computational Linguistics and Artificial Intelligence track thus offers a unique opportunity to acquire in-depth experimental and modeling expertise in the field of natural language processing, a central theme of generative artificial intelligence, whose applications are having a major impact on the current digital transitions that are transforming our societies.
Students who graduate from this program are likely to take up positions in artificial intelligence research and development teams in the public or private sector (from large international corporations to SMEs and start-ups) and also in data driven linguistics. Their education will prepare them to work effectively in highly multidisciplinary environments.
M1 internships
Topic: Internships must be on a computational linguistics topic. We expect students to come into contact with all aspects of study in computational linguistics: from the research question and experimental design to data collection, analysis, and article writing.
Credits: 6 ECTS during the 2nd semester (13 days in a lab)
Evaluation: Full report (20 pages max) and oral presentation at the end of the 2nd semester.
Key words: Computational Linguistics; Machine Learning; Natural Language Processing; Information Retrieval; Machine Translation; Text Mining; Language Models
M1 – Semester 1
Master core curriculum
Ethics in cognitive sciences (3 ECTS), Katie Evans, Anouk Barberousse, Raja Chatila
Master options: 3 to 6 ECTS among these options
Experimental approach (3 ECTS), Christophe Pallier
CORE-2Data camp (3 ECTS), Christophe Pallier, Mehdi Khamassi
PROG-101Introduction to programming (3 ECTS), Sylvain Charron
Track core curriculum
LING-101Introduction au Traitement Automatique des Langues (in French) (3 ECTS), Guillaume Wisniewski
LING-301 Machine Learning for Natural Language Processing: the fundamentals (6 ECTS), Marie Candito
Options : 6 to 9 ECTS among these options
NEURO-101Introduction to Cognitive Neurocience (3 ECTS), Chloé Berland, Pierre Bourdillon
PHILO-101 Scientific reasoning (6 ECTS), Anouk Barberousse
NCIA-101 Introduction to Computational Neuroscience and AI (3 ECTS), Mehdi Khamassi, Benoît Girard
PSYCH-101 Introduction to Cognitive Psychology (3 ECTS), Thérèse Collins
LING-102 Introduction to general linguistics (3 ECTS), Otto Zwartzes (will open in 2026)
Options : 6 ECTS among these options
LING-201 Numerical methods for NLP (3 ECTS), Benoît Crabbé
LING-202 Phonetics (3 ECTS), Hi-Yon Yoo
LING-203 Phonology (3 ECTS), Jalal Al Tamimi
LING-204 Morphology (3 ECTS), Olivier Bonami
LING-205 Syntax (3 ECTS), Anne Abeille
LING-206 Semantics (3 ECTS), Lucia Tovena
LING-207 Linguistic Typology (3 ECTS), Otto Zwartzes (will open in 2026)
M1 – Semester 2
Master core curriculum
Literature (Meta-)review (3 ECTS), Jonathan Vacher
Master options: 3 to 6 ECTS among these options
Experimental approach (3 ECTS), Sylvain Charron
CORE-2Data camp (3 ECTS), Christophe Pallier, Mehdi Khamassi
PROG-202Human experimental workshop (3 ECTS), Mark Wexler
Track core curriculum
LING-208 Theory and pratice of large language models (6 ECTS), Guillaume Wisniewski
LING-209 Computational semantics (6 ECTS), Timothée Bernard
LING-210 Traitement de la parole (in French) (6 ECTS), Nicolas Obin (will open in 2026)
Options : 3 to 6 ECTS among these options
INT-201 Internship (1 day/week) (6 ECTS)
LING-211 Phonological Analysis (3 ECTS), Hi-Yon Yoo
LING-212 Experimental phonology (3 ECTS), Jalal Al Tamimi
LING-213 Theoretical morphology (3 ECTS), Olivier Bonami
LING-214 Topics in minimalist syntax (3 ECTS), Caterina Donati
LING-215 Constraint based syntax (3 ECTS), Anne Abeille
LING-216 Semantics Analysis (3 ECTS), Lucia Tovena
LING-217 Pragmatics (3 ECTS), Lisa Bruneti
Base du Traitement des images (in French) (6 ECTS), Dominique Béréziat
Intelligence Artificielle et Manipulation Symbolique de l’Information (6 ECTS), Christophe Marsala, Gauvain Bourgne, Jean-Gabriel Ganascia
INFO-SU-4 Interfaces Humain-Machine (in French) (6 ECTS), Gilles Bailly, Baptiste Caramiaux
M2 – Semester 3
Master core curriculum
INT-301 Internship preparation (1 day/week) (6 ECTS)
Options : 24 ECTS among these options
LING-218 Computational language modeling and cognition (6 ECTS), Benoit Crabbé
LING-219 Topic Modeling (3 ECTS), François Yvon
LING-220 Multilingual natural language processing and machine translation (3ECTS), Guillaume Wisniewski
LING-221 Advanced topics in natural language processing (3 ECTS), Timothée Bernard
LING-222 Current topics in natural language processing and society (3ECTS), Marie Candito
LING-223 Broadening in data science and NLP 1 (3ECTS), Marie Candito
LING-224 Broadening in data science and NLP 2 (3 ECTS), Marie Candito
LING-225 Broadening in data science and NLP 3 (3 ECTS), Marie Candito
LING-226 Topics in phonological theories (3 ECTS), Ioana Chitoran
LING-227 Topics in prosody (3 ECTS), Hiyon Yoo
LING-228 Advanced morphology (3 ECTS), Olivier Bonami
LING-229 Theory driven experimental syntax (3 ECTS), Hiyon Yoo
LING-230 Advanced experimental syntax (3 ECTS), Anne Abeillé
LING-231 Advanced semantics and pragmatics (3 ECTS), Lucia Tovena
LING-232 Techniques in experimental and computational phonology (3 ECTS), Jalal Al Tamimi
LING-233 Experimental design and Psycholinguistics (3 ECTS), Barbara Hemforth
LING-234 Phonetics (3 ECTS), Hi-Yon Yoo
LING-235 Phonology (3 ECTS), Jalal Al Tamimi
LING-236 Morphology (3 ECTS), Olivier Bonami
LING-237 Syntax (3 ECTS), Caterina Donati
LING-238 Semantics (3ECTS), Lucia Tovena
LING-239 Linguistic Typology (3 ECTS), Otto Zwartzes
MVA-1 Algorithms for speech and natural language processing (6 ECTS), Emmanuel Dupoux
2 Large Language Models (3 ECTS), Benjamin Piwowarski
INFO-SU-7 AMAL: Advanced MAchine Learning & Deep Learning (6 ECTS), Patrick Gallinari
M2 – Semester 4
Master core curriculum
INT-401 Internship (full time) (30 ECTS)