Space applications
training courses

BUT Sciences des Données, Parcours Exploration et Modélisation Statistique (EMS)

• Organisation : IUT 2 Grenoble - Université Grenoble Alpes
  (Université Grenoble Alpes)
• Way of training : Initial education - Sandwich/Apprenticeship training
• Language(s): French
• Place: Grenoble (French Regions: Auvergne-Rhône-Alpes)
• Prepared diploma/grade/title: BUT (three-year technological university degree)
• 1st required level : French baccalauréat + 0

Course Details

Objectives : The EMS course aims to train professionals competent in the collection, processing and statistical analysis of data. Their skills allow them to participate in the definition and collection of relevant data to respond to a given problem, in the choice of appropriate statistical tools according to the situations encountered, and to implement these tools within the framework of an analysis or a modeling and produce relevant and rigorous results in the form of reports, tables and graphs.

Information: the licenses below are included in this BUT course:
Professional degree in decision-making and statistics professions - Statistical studies, survey and marketing course
Professional degree in decision-making and statistics professions - Statistical studies and geographic information systems track
Professional license IT professions: information systems and data management - Big-data course

Degree Level (EU) : 6 - (EQC level or equivalent)

Targeted careers : The Exploration and Statistical Modeling (EMS) course prepares students to collect, process and analyze data. They can be recruited as statistician assistant, data scientist assistant, marketing research assistant, analysis and reporting manager, statistical study manager, or even statistical developer.

Duration and terms : 3 years

Dedicated web site : http://tinyurl.com/mw3ba235

Dedicated web site : https://iut2.univ-grenoble-alpes.fr/formations/bachelors-universitaires-de-technologie/but-science-des-donnees-794862.kjsp?RH=1608220848991 (IUT2)

Applications

• Environment and Land Management (Environmental protection, agriculture, biodiversity, climate changes; Resources, land-use planning, infrastructures)

Space Technologies and Scientific Disciplines

• Data processing and analysis (Signal and image processing, big data, learning algorithms, artificial intelligence...)
• Earth observation (Remote sensing, GIS, geomatics)