Le parcours IAAA introduit les avancées les plus récentes en intelligence artificielle et forme à l'exploitation des méthodes et techniques associées dans des applications innovantes. Les thèmes abordés sont l'apprentissage automatique, l’apprentissage profond, le traitement automatique du langage naturel, la modélisation et de la résolution de problèmes à base de contraintes, et la représentation et le traitement des connaissances. Ces thèmes s’inscrivent notamment dans le cadre de la science des données et de l’informatique fondamentale.
Pédagogie
AIMS
The IAAA pathway introduces the most recent advances in artificial intelligence and trains students to use the associated methods and techniques in innovative applications. The themes addressed are machine learning, deep learning, automatic natural language processing, modelling and solving constraint-based problems, and knowledge representation and processing. In particular, these themes are part of data science and fundamental computing.
The IAAA pathway is designed for students who wish to develop their knowledge and skills in the field of IAAA.
The IAAA course shares teaching units with the data science master's degree in applied mathematics, with the Science des Données option at the École Centrale Marseille, and with the master's degree in cognitive sciences from the ILCB convergence institute on the learning aspects à the confluence of brain and computer thèmes, and will give rise à joint projects with étudiants across all of the institute's disciplines.
The IAAA pathway is strongly oriented towards « research » and « research and development » with strong débouchéIt also enables a company to be directly involved in projects developing applications involving AI-based technologies.
This pathway will be internationally oriented, in particular through the recruitment of foreign students via Ecole Centrale Marseille.
Targets:
- R&D engineer
- Monitoring or research officer, Teacher-researcher or researcher
- Project manager
- Study and development engineer
- « Data scientist » or « Data analyst »
FUNDAMENTAL PREREQUISITES
Bachelor's degree in Computer Science, Mathematics-Computer Science or Mathematics.
FUNDAMENTAL PREREQUISITES
It is recommended that you have already practised programming in Python and C. Knowledge of undergraduate mathematics in linear algebra, probabilities and statistics is also a plus. Being able to work in a Linux environment is also a plus.
LEARNING SITES
- SCIENCES, Marseille Luminy
- SCIENCES, Marseille St-Jérôme
LEARNING AND RESEARCH
This course is supported by the QARMA, TALEP and COALA teams at the LIS laboratory. Much of the content draws on the research work of these teams. The course is designed for both research and professional purposes. Candidates can join a research team in industry or continue their thesis in academia.
PROFESSIONAL SKILLS TO BE ACQUIRED
Create or exploit innovative methods and algorithms in the field of machine learning, deep learning, automatic natural language processing, constraint-based problem modelling and solving, and knowledge representation and processing.
NSF DOMAINS
- 114B Modèles mathématiques ; Informatique mathématique (fr)
- 326M Informatique, traitement de l'information (fr)
- 326T Programmation, mise en place de logiciels (fr)
LEARNING COURSES LIST
Inscription
SCHOOL REGISTRATION
Typical courses can be access by- Initial Formation
- Continious formation
