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Master of Data Science


The objective of the Master of Data Science is to provide initial training that will meet the growing demand for data science experts, providing students with the technical skills needed to solve complex problems using data. Graduates will be prepared for a variety of professional functions requiring data analysis skills in the health, economic, social network or financial sectors.

The training is based on a multidisciplinary approach that includes mathematics and computer science. Mathematics provides the fundamental tools and theoretical bases needed to design and analyse procedures, while computer science enables these procedures to be translated into algorithms and to manage the organisation of calculations and the manipulation of large databases.

The applications relate to problems arising from physics, life sciences and the industrial world. They will illustrate how statistics, machine learning, deep learning and data visualisation methods are used by researchers and industrialists in their scientific analyses and decision-making.


At the end of the programme, students will be able to :

  • Master statistical methods, understand the underlying assumptions, correctly interpret results and adapt methods to new contexts
  • Effectively apply the relevant tools for the management of different database structures for data pre-processing and collection
  • Analyse complex problems from other scientific and technological fields and plan strategies for their resolution
  • Demonstrate a broad understanding of the fundamental and specialised fields of information technology
  • Explore and extract knowledge from large and/or complex information bases
  • Construct mathematical and computer models for complex systems
  • Optimise static/dynamic multi-objective and multi-stress problems
  • Address related knowledge domains and recognize interconnections
  • Communicate information accurately and effectively to an audience of experts and non-experts
  • Assess and discuss the risks of making a wrong decision based on available information
  • Express opinions based on scientific and ethical considerations