The computer science developers and designers of tomorrow face two major challenges:
increasingly complex computer science systems
increasingly varied areas of application
In order to meet these challenges, future diploma holders should:
master real computer science technologies but also keep up with their constant progress
work as part of multidisciplinary teams that take into account non-technical issues
This master 60 aims at the in-depth understanding of concepts and the acquisition of thinking and abstraction skills. This theoretical approach is supplemented by the application of concepts which takes an important place in the training. The program therefore includes many projects and works.
Except for exceptions specified in the detailed program, all the courses of the program are given in English, the command of this language being essential in the field of data processing. This offers French-speaking students the opportunity to practice English intensively during their training.
On successful completion of this programme, each student is able to :
This Master’s degree programme aims to provide students with advanced knowledge and is based on the fundamentals of computer science acquired in the Bachelor’s degree programme. A diversity of subjects are offered in the common curriculum:
M.1. Networking;
M.2. Programming languages;
M.3. Software engineering;
M.4. Artificial intelligence.
2.1. Analyse a problem to solve or functional needs to be met and formulate a corresponding specifications note.
2.2. Model a problem and design one or more technical solutions in line with the specifications note.
2.5. Come up with recommendations to improve the solution.
2.6. Think disruptively and creatively, open to plurality.
3.1. Frame and explain the project’s objectives (in terms of performance indicators) while taking into account its issues and constraints.
3.2. Collaborate on a work schedule, deadlines and roles.
3.3. Work in a multi/inter/transdisciplinary environment with peers holding different points of view; manage any resulting disagreement or conflicts, identify the contributions and limits of each discipline, dialogue on the same project.
3.4. Make team decisions and assume the consequences of these decisions (whether they are about technical solutions or the division of labour to complete a project).
4.1. Identify the needs of all parties: question, listen and understand all aspects of their request and not just the technical aspects.
4.2. Present your arguments, advise and adapt to the language of your interlocutors: technicians, colleagues, clients, superiors, specialists from other disciplines or general public.
4.3. Communicate through graphics and diagrams: interpret a diagram, present project results, structure information
4.4. Read and analyse different technical documents (rules, plans, specification notes)
4.5. Draft documents that take into account contextual requirements and social conventions
4.6. Make a convincing oral presentation using modern communication techniques
5.1. Acquire a knowledge base on the socio-ecological issues and use multi-criteria tools to evaluate the sustainability of a technology, in quantitative and/or qualitative terms.
5.2. Define, specify and analyze a problem in all its complexity, taking into account its various dimensions (social, ethical, environmental, etc.), scales (time, place) and uncertainty.
5.3. Identify, propose and activate engineering levers that can contribute to sustainable development and transition (eco-design, robustness, circularity, energy efficiency, etc.).
5.4. Demonstrate critical awareness of a technical solution in order to verify its robustness and minimize the risks that may occur during implementation, be aware of its limitations, and take a personal stand on ethical, environmental and societal issues.
5.5. Evaluate oneself and independently develop necessary skills to remain knowledgeable in the field.