Space applications
training courses

Mastère Data Engineer

• Organisations :
  • Campus YNOV Bordeaux - École des métiers du digital
  • Campus YNOV Aix-en-Provence - Ecole des métiers du digital
  • Campus YNOV Paris - Ecole des métiers du digital
  • Campus YNOV Montpellier
• Way of training : Initial education - Sandwich/Apprenticeship training
• Language(s): French
• Place: Bordeaux (33) et nombreux campus
• Prepared diploma/grade/title: Mastère, Mastaire,... (master degree level from a French academic institution)
• 1st required level : French baccalauréat + 3
• This training is included in RNCP / RS

Course Details

Objectives : Master Data Engineer aims to prepare you for careers in data science. Big Data, Machine learning, Dataming and visualization, data science… You will know these concepts like the back of your hand. Eventually, you will be responsible for the management, analysis and exploitation of massive data collected by different channels within a company. The goal ? Restore this data in the form of a forecast, so as to make it an element of strategic decision-making.

This Master Data Engineer can be done on a work-study basis, so as to apply the training directly in the company to concrete cases.

Our work-study Data Engineer Master's will offer you very specific lessons. During the two years that make up your Master's in Data Engineer, we will equip you with precise technical knowledge, develop your thinking skills to make it ever more rigorous, in order to make you an expert in data science, a buoyant field (which includes in particular the big data) in the professional world.

Concerned campuses::
Aix-en-Provence, Bordeaux, Lyon, Nantes, Paris, Montpellier, Lille, et Rennes

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

Prerequisites : Bac +3 like the Computer Science Bachelor

Targeted careers : Data Scientist, Data Analyst, Chief Data Office, Marketing Data Officer…

Dedicated web site : https://ynov-bordeaux.com/mastere-data-engineer/

Space Technologies and Scientific Disciplines

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