www.cnes.fr www.issat.com
Space Education Catalogue

Master parcours Mathématiques et informatique pour le Big Data

• Organisation : Collège STEE, Université de Pau et des Pays de l'Adour
  (Université de Pau et des Pays de l'Adour (UPPA))
• Way of training : Initial education - Sandwich/Apprenticeship training
• Language(s): French
• Place: Pau, Anglet (French Regions: Nouvelle-Aquitaine)
• Prepared diploma/grade/title: Master or DNM: French National Master Degree
• 1st required level : French baccalauréat + 3

Course Details

Objectives : The trades targeted by this training concern the entire chain of storage, processing and exploitation of data. In particular those which address the technical and methodological aspects linked to the hardware or software infrastructure, the algorithms for processing and prediction, the development and exploitation of the results. The training targets the Data Analyst and Data Scientist trades but also aims to respond to the challenge posed by big data research

Degree Level (EU) : 7 - (EQC level or equivalent)

Prerequisites : The candidate must be able to follow a master's degree in mathematics AND a master's degree in computer science

Acquired skills during the training : Responding to the challenge posed by Big Data requires new skills related to the data science field combining solid knowledge in computer science and mathematics as well as a corporate culture. Graduates will in particular be able to integrate all the sectors of activity concerned by skills such as: designing architectures making it possible to process large volumes of data and proposing solutions for accessing these data; monitor data flows from their source to their destination; compose methods, means and tools to help decision-making; propose, adapt and develop the necessary algotithms in order to extract relevant information from endogenous and exogenous data.

Duration and terms : Admission by right for students enrolled in the Cursus Master in Mathematics and Computer Engineering.

Admission in M1 only on file for other students:

holders of a license in mathematics and computer science or equivalent,
holders of a CTI engineering degree with solid training in computer science or having validated at least the first year of the engineering cycle.

Dedicated web site : https://tinyurl.com/yc7vndey

Disciplines

• Engineering Sciences

Topics

• 11 - Computer Science, Applied Mathematics, Modelling, Optimisation, Digital and Data Sciences, Big Data, Cryptography, Cybersecurity, Artificial Intelligence