Space applications
training courses

Master Data Science (DS)

• Organisation : Faculté des Sciences, Université d'Angers
  (Université d'Angers)
• Way of training : Initial education - Life-long learning - Sandwich/Apprenticeship training
• Language(s): French
• Place: Département de Mathématiques, Angers (French Regions: Ile-de-France)
• Prepared diploma/grade/title: Master or DNM: French National Master Degree
• 1st required level : French baccalauréat + 3

Course Details

Objectives : Data Science refers to a discipline at the interface between mathematical, statistical and computer modeling, born from the growing need to process and exploit big data. Data science is now the essential decision-making tool in extremely varied fields of activity: banking, finance, insurance, e-commerce and mass distribution, communication and marketing, health, agri-food, aeronautics and defense , internet of things and telecoms, etc.
The Data Science (DS) course of the master's degree in Mathematics and Applications is a level one training (Bac+5). It aims to train data-scientist executives capable of implementing the mathematical and computer techniques inherent to this profession, also possessing professional skills specific to the sectors of activity targeted by the choice of options.

Public concerned : students

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

Admission requirements : students with a bachelor's degree in mathematics, a bachelor's degree in mathematics and computer science applied to the humanities and social sciences (oriented course in applied mathematics), or an equivalent level.

Notes : The second year of master M2-DS is open to work-study, apprenticeship or under professionalization contract.

Dedicated web site : https://formations.univ-angers.fr/fr/offre-de-formation/master-lmd-MLMD/sciences-technologies-sante-STS/master-mathematiques-et-applications-KV26XNFS/parcours-data-sciences-L09QAC4H.html

Space Technologies and Scientific Disciplines

• Data processing and analysis (Signal and image processing, big data, learning algorithms, artificial intelligence...)