La première partie de la formation est commune et est constituée d’unités d’enseignement sur les concepts de base du domaine de l’EEA. La deuxième partie est dédiée à la spécialisation. Il s’agit de maîtriser les méthodologies de régulation et d’asservissement des procédés ainsi que de leur surveillance à travers des techniques du diagnostic. Les approches explorées sont fondées sur l’utilisation des méthodes avancées de l’automatique.
Pédagogie
AIMS
The aim is to give students a dual skill set. A scientific skill oriented towards methods based on modelling, data analysis and artificial intelligence (machine learning and deep learning) for diagnosing faults and predicting system degradation. Professional experience, gained through work placements in industry, will enable them to gain knowledge of the fields of application, with the aim of being able to apply these approaches to formalise and solve a variety of problems relating to monitoring, diagnosis, reliability and maintenance
TARGETED STUDENTS
The first year (M1) of the master's programme is essentially open to students holding a Bachelor's degree in Engineering Sciences or any equivalent general or professional training including a significant part of the field of EEEA, applied mathematics. The S3AD M2 is for students with an M1 in EEEA, applied mathematics, statistics, data science and computer science.
ADMISSION CONDITIONS
For M1s, applications will be made online via the MonMaster platform with two recruitment routes: initial training and sandwich courses.
M2 selection will be subject to a different process. Initially, students from our M1 who have chosen the S3AD pathway will be accepted automatically, and we will open up the possibility of direct entry to the M2 S3AD apprenticeship scheme. These M2 students from other courses will be recruited on the basis of a review of their application, followed by a 20-minute interview with the teaching team
FUNDAMENTAL PREREQUISITES
- Modification, regulation, automation, supervision
- Applied mathematics (linear algebra, analysis, optimisation)
- Data analysis
FUNDAMENTAL PREREQUISITES
- Systems theory
- Applied Physics
- Dynamic systems
STRUCTURE AND ORGANISATION
Our organisation makes it possible to obtain the EEEA masters course S3AD with several statuses depending on the origins and expectations of the étudiants : Initial training, continuing education, apprenticeship and professionalization contract.
The first year of the master's degree offers a core of disciplinary training enabling students to acquire the basic skills required in the field of EEEA.
Teaching in M2 is organised as lectures, tutorials or practical work.
For the sandwich course, there will be 30 weeks in a company and 17 weeks at the university. The alternation will be 2 weeks at university followed by 2 weeks in the company and, from mid-May, 14 weeks in the company.
For students in initial training, it carries out an industrial project which is carried out over two periods: At the company, with the definition of the problem and the collection of data, and at the university, with the development of the project based on the data collected and the lessons learned.
LEARNING SITES
- SCIENCES, Marseille St-Jérôme
LEARNING AND RESEARCH
The teaching team is made up of teacher-researchers from the LIS UMR CNRS 7020 and more particularly from the DiaPRO team, which works on major collaborative projects in the field of data analysis monitoring with SMEs and major groups. These industrial links will be brought to the forefront of the training programme, either through presentations by professionals or by hosting and recruiting our students on apprenticeship contracts
PROFESSIONAL SKILLS TO BE ACQUIRED
The Surveillance, Systems and Data Analysis (S3AD) pathway will offer future graduates a dual skill set. A scientific skill focused on model-based methods, data analysis and artificial intelligence (machine learning and deep learning) for diagnosing faults and predicting system degradation. Professional experience, gained through work placements in industry, will enable them to gain knowledge of the fields of application, with the aim of being able to apply these approaches to formalise and solve a variety of problems relating to monitoring, diagnosis, reliability and maintenance
Inscription
ADMISSION CONDITIONS
For M1s, applications will be made online via the MonMaster platform with two recruitment routes: initial training and sandwich courses.
M2 selection will be subject to a different process. Initially, students from our M1 who have chosen the S3AD pathway will be accepted automatically, and we will open up the possibility of direct entry to the M2 S3AD apprenticeship scheme. These M2 students from other courses will be recruited on the basis of a review of their application, followed by a 20-minute interview with the teaching team
SCHOOL REGISTRATION
Typical courses can be access by
Responsable du parcours
- Bouchra OULADSINE — Responsable)
- El mostafa EL ADEL — Co-responsable)
