Master's degree Computer Science
Entry requirements
The course is open to holders of a Licence in computer science.
Benefits of the program
The Master's can be studied in work-study format from the first year.
The course places emphasis on technical skills, which are assessed through individual machine exams and multiple group projects. These skills are placed into practice during the mandatory end-of-year work placement.
Most of the teaching staff are researchers in a highly reputed research laboratory, LIGM, which addresses many aspects of computer science, both theoretical themes and practical applications. One of the course's advantages are these cutting-edge research skills.
The Master's in Computer Science is part of the Bézout SFRI Graduate Program, which undertakes initiatives to encourage Master's students to work in research. The programme also offers academic merit scholarships for M2.
After graduating, most students are offered a permanent contract following their work-study programme or work placement.
Acquired skills
M1 provides the basic skills needed for the various programmes offered in M2. This mainly includes advanced aspects of object-oriented programming, databases and network programming, as well as fundamental notions of computer science: algorithm complexity, combinatory optimisation and cryptography.
Furthermore, it offers initial classes for the various M2 programmes: Internet of Things, introduction to image processing, data analysis, and classes combining mathematics and computer science.
International
Students can spend a semester abroad as part of the ERASMUS programme or the partnership with University of Palermo.
Capacities
72
Course venue
Your future career
This Master's targets careers in IT project management, IT development (system design and application development), research and development, etc.
Students wishing to undertake further studies generally pursue one of the M2 programmes at our university.
Four of the programmes target specific fields of application: digital images (medical imaging, video games, digital post-production, etc.), software development (software editors, IT service companies, large companies developing proprietary software, etc.), Internet of Things (smart connected systems, embedded applications, networks of connected objects), and artificial intelligence.
The fifth track primarily targets research careers, while preparing students for IT project management positions as well. PhD candidates can focus on an area of research during projects (research and technological innovation projects, tutored projects) and during the M2 work placement.
Professional integration
Most students continue with M2 and find a job after their work placement.
Study objectives
The objective of M1 is to provide a solid foundation for the subjects studied in M2.
Major thematics of study
Programming, networks, digital images.
Calendar
Three-month work placement from May onwards.
Work-study schedule: Two days at a company and three days at university.
Back-to-school date
09-16-2024
Semester 1
| Courses | ECTS | CM | TD | TP |
|---|---|---|---|---|
|
=IF(OR(B24="ANAD",B24="BLOC"),Feuil2!$B$263,IF(OR(B24="SEM",B24="ECUE",B24="UE",B24="MATI",B24="COMP"),Feuil2!$B$265,""))
27->Informatique | 6 | 24h | 24h | |
|
Méthode et modélisation pour l'optimisation
Modelling and resolution of optimisation problems : In this course, we formalise various optimisation problems (resource allocation, transportation problems, graph colouring, ...) as linear programs or as SAT (boolean satisfiability) instances. For both types of problems, there exist today highly optimised solvers that we wish to leverage. We study the simplex algorithm and duality for linear programming and look at the DPLL algorithm and CDCL-based solvers for SAT | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h | |
|
=IF(OR(B28="ANAD",B28="BLOC"),Feuil2!$B$263,IF(OR(B28="SEM",B28="ECUE",B28="UE",B28="MATI",B28="COMP"),Feuil2!$B$265,""))
27->Informatique | 3 | 30h | ||
|
Python et Langages de scripts
Introduction and advanced usage of Python : syntax, types (numbers, strings, lists, tuples, sets, dictionnaries), classes, and exploration of the most common modules of the standard library : sys, os (system), re (regular expressions), urrlib (http), HTMLParser (html processing), itertools (efficient iterations), Cycthon (optimized compiler), socket (network). | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h | |
|
Ressources linguistique
The aim is to familiarize computer scientists with linguistic constraints. Modeling linguistic datas. The linguistic description (grammatical, morphological, syntactic and semantic) is intended to be used in computer applications. The transition from linguistic description to computer realisation is facilitated by the use of finite automata. | 3 | 12h | 12h | |
|
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27->Informatique | 3 | 12h | 12h |
Semester 2
| Courses | ECTS | CM | TD | TP |
|---|---|---|---|---|
|
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27->Informatique | 3 | 12h | 12h | |
|
Images et notions fondamentales
This course introduces the fundamental techniques of manipulating and processing digital images. We first discuss how digital images are structured and stored, and then go through the geometric and colorimetric transformations. We devote one session to convolution filtering and another to frequency analysis, in particular by Fourier transforms and wavelet transforms. | 3 | 12h | 12h | |
|
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27->Informatique | 6 | 24h | ||
|
O
Option du second semestre portant assez largement sur l'étude des graphes (ou autres structures discrètes), des points de vue probabiliste (méthode probabiliste, concentration), structurel (théorie de Ramsey notamment), algorithmique (structures de données, algorithmes randomisés), éventuellement spectral (expanseurs). | 3 | 12h | 12h | |
|
Programmation générique en C++
ava. After a talk on real time applications and the specific behavior of Java, we describe different models of real time taskes, different schedulers, we show how to analyse possibility of scheduling in the case of fixed priority scheduling. We study the case of synchronized tasks with two algorithms of synchronisation (PIP and PEP) and their influence for the analize of possibility of scheduling. We end with the problem of admiting non-periodic taskes in periodic server | 5 | 8h | 28h | |
|
Machine Learning
| 3 | 12h | 12h | |
|
Stage
27->Informatique | 7 | |||
|
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| 12h | 12h | ||
|
GESTION DE PROJET ET COMMUNICATION
| 3 | 12h | 12h | |
|
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Option du second semestre portant assez largement sur l'étude des graphes (ou autres structures discrètes), des points de vue probabiliste (méthode probabiliste, concentration), structurel (théorie de Ramsey notamment), algorithmique (structures de données, algorithmes randomisés), éventuellement spectral (expanseurs). | 3 | 12h | 12h | |
|
PERL - Langages de scripts professionnels
This course presents the flexibility, high power and rich libraries of PERL. After the basics of the language we present advanced programming with regular expressions, references, modules, genericity, the Perl modules with network communication sockets, threads, system calls and time management, email management, web queries, databases and dynamic web. | 3 | 12h | 12h | |
|
O
27->Informatique | 3 | 12h | 12h |
CARAYOL Arnaud (M1-M2)
PIVOTEAU Carine (M1)
ZERIZER Razika (M1)
Partners
Université de Palerme