ECTS
120 credits
Duration
2 years
Training structure
Faculty of Science
Language(s) of instruction
French
Presentation
This Artificial Intelligence and Data Science program trains specialists with a high level of programming skills in the design and development of intelligent information systems and automatic data analysis. The training includes four closely related aspects:
1) learning, extraction or acquisition of data (machine learning)
2) automatic analysis of data, particularly textual data, i.e. automatic processing of natural language (natural language processing)
3) representation and storage of data and their semantics
4) data processing and reasoning on semantic knowledge, for example, for decision support.
The programming of these methods is present in each course as well as in the course of software engineering of the path.
For students who have validated a Bachelor's degree in Computer Science with the CMI label (Cursus Master Ingénierie), it is possible to 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 Master's Degree in Computer Science Engineering is a demanding and reinforced 5-year program that completes the Bachelor's - Master's Degree in Computer Science program by adding specific courses. The CMI has been developed as a complementary model for training in engineering professions through a five-year diploma course leading to a Master's degree in Engineering, corresponding to the international Master of Engineering model. This CMI label guarantees a coherent and demanding university training program for the profession of expert engineer. 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.) for the Master of Engineering - Computer Science program. The CMI Computer Science is open to Master 2 students on a sandwich basis.
For students wishing to co-diploma IAE Master Management of Technology and Science: possibility offered (on file) to achieve in parallel with the initial training a management training giving the degree of Master in Management of Technology and Science. Over the two years of training, the curriculum alternates courses in computer science (taught by the FdS) and management (taught by the IAE) with a common internship validated by both components in the second year. This co-diplomation allows students to exit with the master Computer Science and the master Management of Technologies and Sciences.
Objectives
The objective 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 degree program are able to design and develop software for the automatic analysis of large amounts of data, particularly textual data, as well as algorithms for the automatic acquisition of data and the representation of their semantics; they are also able to program the methods and algorithms of Big Data, Machine Learning and Artificial Intelligence; they also know how to model and automate reasoning about data and their semantics.
Know-how and skills
The course provides a balanced mix of theoretical and conceptual foundations, and training through programming in the most current technologies, which allows for rapid professional integration as well as the scientific distance necessary for adaptability to future developments in computer science. The content of the program allows students to appropriate and implement the methods and tools of language, data and knowledge engineering, between artificial intelligence, machine learning and data management, while reinforcing their programming skills as well as their mastery of information systems and web technologies.
Organization
Knowledge control
https://mcc.umontpellier.fr/ groups all the teaching units (UE) and their knowledge control methods.
Open in alternation
Type of contract | Apprenticeship contract, Professionalization contract |
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The second year(M2) can be done on a sandwich basis, via professionalization or apprenticeship contracts. The alternating student becomes an employee for the duration of his or her M2 (under contract generally from September 1 to August 31). The academic year takes the following form: during the 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 in the company (1 week in November, 2 weeks in December, and from the last week of January to August 31; this makes a presence in the company of 8 months out of 12).
We remind you here that a professionalization or apprenticeship contract is a tripartite contract between student, company and university: the agreement of the head of the program is necessary; his opinion is based on the academic results of the M1 and on the opinion of the course leaders. Thus, excellent results in M1 are expected in order to have a favorable opinion on the alternation.
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 warehouses and Big-Data
Machine learning 1 (classical 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
Epistemology of computer science
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 internship
30 credits
Admission
Conditions of access
The Master's degree is open to holders of a computer science degree (or equivalent).
How to register
Applications are made on the following platforms:
French & European students:
- For the M1, follow the procedure " My Master " from 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 "Studies in 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 related to artificial intelligence, machine learning, data science (BigData) or natural language processing, i.e. related 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