Active learning and soft skills
You will play an active role in your training. The teaching approach is a balanced mix of lectures, exercises, projects to be carried out alone or in groups. The teaching methods are varied. Sometimes, you will be encouraged to discover concepts or techniques on your own, with the teaching staff acting more as a resource to support your learning.
In other instances, teaching will be more transmissive, giving you the keys you need to complete the tasks ahead. An emphasis is placed on non-technical skills (autonomy, organisational skills, time management, communication in various forms, etc.). Thanks in particular to a teaching approach that emphasises project activities (including a large-scale project that puts groups of students in semi-professional situations), the course trains you to develop a critical mind capable of designing, modelling, implementing and validating complex IT systems.
Languages
The lingua franca of data science is mainly English. English is used throughout the programme to help you master the language, which will facilitate your integration into the world of work. Course support materials and supervision are in English. You may, nevertheless, ask questions or take the exam in French if you wish. The programme also offers you the opportunity to take language courses and participate in exchange programmes abroad.
Interdisciplinarity
Data scientists, like many academics over the course of their careers, will find themselves managing projects and teams, and engaging with the complex socio-economic context in which data science operates. You will therefore be encouraged to broaden your training to include other disciplines through elective courses or certain options such as interdisciplinary training in entrepreneurship.