ECTS
120 credits
Duration
2 years
Training structure
Faculty of Science
Language(s) of instruction
French
Presentation
This course in Artificial Intelligence and Data Science trains specialists with a high level of programming skills in the design and development of intelligent information systems and automatic data analysis. The training covers four closely related aspects:
1) learning, extraction or acquisition of data (machine learning)
2) automatic analysis of data, particularly textual data, i.e. natural language processing
3) representation and storage of data and its semantics
4) data processing and reasoning on semantic knowledge, for example for decision support.
Programming these methods is present in every course, as well as in the course's software engineering courses.
Students who have completed a CMI (Cursus Master Ingénierie)accredited bachelor's degree in computer science can follow the CMI curriculum in the Algorithmics (Algo), Software Engineering (GL), Imagine (Imagine) and Artificial Intelligence and Data Science (IASD) courses. As a reminder, the CMI Master's degree in Computer Science Engineering is a demanding, reinforced 5-year course that complements the Bachelor's - Master's degree in Computer Science by adding specific courses. The CMI has been designed as a complementary training model for engineering professions, with a five-year diploma course leading to the title of Master in Engineering, corresponding to the international Master of Engineering model. The CMI label guarantees a coherent and demanding university training program for expert engineers. Upon completion of the CMI Informatique, graduates obtain a Master of Management from the Institut d'Administration des Entreprises (IAE), the Figure network label, as well as a university diploma (D.U.) in the Master of Engineering - Computer Science curriculum. The CMI Informatique is open to Master 2 students on a sandwich course.
For students wishing to apply for the IAE Master in Technology and Science Management degree, the possibility is offered (subject to application) of taking a management course in parallel with the initial course, leading to a Master's degree in Technology and Science Management. Over the two years of the program, the curriculum alternates computer science courses (taught by the FdS) and management courses (taught by the IAE), with a joint internship validated by both departments in the second year. This co-diplomation enables students to exit with a Master's degree in Computer Science and a Master's degree in Technology and Science Management.
Objectives
The aim of this course is to train high-level computer science experts and managers in programming, in the field of artificial intelligence and data science, mastering both statistical and formal methods. Graduates of the Artificial Intelligence and Data Science master's program are able to design and develop software for the automatic analysis of large volumes of data, particularly textual data, as well as algorithms for the automatic acquisition of data and the representation of its semantics; they are also able to program the methods and algorithms of Big Data, Machine Learning and Artificial Intelligence; and they know how to model and automate reasoning about data and its semantics.
Know-how and skills
The course provides a balanced mix of theoretical and conceptual foundations, and training in the most up-to-date technologies through programming, enabling both rapid professional integration and the scientific distance needed to adapt to future developments in computer science. The course content enables students to acquire and apply the methods and tools of language, data and knowledge engineering, including artificial intelligence, machine learning and data management, while reinforcing their programming skills and their mastery of information systems and web technologies.
Organization
Knowledge control
https://mcc.umontpellier.fr/ groups together all the teaching units (UE) and their assessment procedures.
Open on a sandwich basis
Contract type | Apprenticeship contract, Professionalization contract |
|---|
The second year(M2) can be taken on a sandwich course, via a professionalization or apprenticeship contract. Alternating students become employees for the duration of their M2 (under contract, generally from September 1 to August 31). The academic year takes the following form: during the university course/TD/TP period, the alternating student is at the faculty to follow the courses; during the university vacation and internship periods, the alternating student is at the company (1 week in November, 2 weeks in December, and from the last week of January to August 31; making a company presence of 8 months out of 12).
It should be remembered that a professionalization or apprenticeship contract is a three-way contract between student/company/university: the approval of the department head is required; his or her opinion is based on the academic results of the M1 and the opinion of the course leaders. Excellent results in M1 are thus expected in order to obtain a favorable opinion on the sandwich course.
Program
Select a program
M1 - Artificial intelligence and data science
English S1
2 creditsProbability, statistics
2 creditsFoundations of symbolic AI
4 creditsCHOICE 1
4 creditsYour choice: 1 of 4
Distributed software architectures
4 creditsCryptographic foundations for security
4 creditsPOA/SMA
4 creditsGraphs: structures and algorithms
4 credits
Algebra, geometry, transformation, numerical calculation
2 creditsLogic, computability and complexity
4 creditsSoftware engineering
4 creditsDistributed programming
4 creditsData warehousing and Big-Data
Machine learning 1 (classic methods)
4 creditsT.E.R
4 creditsEnglish S2
2 creditsSemantic data processing
4 creditsLogic for software engineering and AI
4 creditsDevelopment and programming for mobile devices
4 creditsNatural language 1 (syntax)
4 creditsCHOICE 2
4 creditsYour choice: 1 of 2
Computer science epistemology
4 creditsProject management
4 credits
M2 - Artificial intelligence and data science
Natural language 2 (word and sentence semantics)
4 creditsDecision support
4 creditsMachine learning 2 (advanced methods)
4 creditsDatabase theory and knowledge
4 creditsConferences
2 creditsData management beyond SQL (NoSQL)
4 creditsCHOICE 1
8 creditsChoice of 2 out of 3
Database administration
4 creditsAdvanced mobile, IoT and embedded development
4 creditsConstraints
4 credits
CHOICE 2
30 creditsYour choice: 1 of 2
Industrial internship
30 creditsAcademic training
30 credits
Admission
Access conditions
The Master's program is open to holders of a bachelor's degree in computer science (or equivalent).
How to register
Applications can be submitted on the following platforms:
French & European students :
- For M1, follow the "My Master" procedure on the website: https: //www.monmaster.gouv.fr/
- For M2, students must submit their application via the e-candidat application: https: //candidature.umontpellier.fr/candidature
International students from outside the EU: follow the "Études en France" procedure for M2: https: //pastel.diplomatie.gouv.fr/etudesenfrance/dyn/public/authentification/login.html
Capacity
And then
Further studies
Doctorate (competitive examination).
Professional integration
Sectors of activity:All fields of activity linked to artificial intelligence, machine learning, BigData or natural language processing, i.e. linked to the management, exploitation and computer processing of documents and data.
Job types :Data Scientist (BigData engineer) , NLP engineer / scientist, AI engineer / researcher, ML engineer, ML expert, Knowledge engineer