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Description

Objectives in terms of knowledge (course content) :

This teaching is intended to raise the student's awareness of the problems associated with the automatic processing of very large quantities of data in different fields of human activity (economics, communication, biology ...). The objective is to show that the implementation of a high-throughput experimental strategy is closely linked to the use of adapted IT tools. The teaching is mainly based on case studies, following presentations by different actors and professionals dealing with the issue of "big data".

Compétences visées

Objectives in terms of skills :

  • Assess hardware and software needs in a project
  • Finding skills in the field of data processing
  • Draft specifications for an IT service company
  • Monitor the evolution of this sector of activity

Contact

Responsable(s) de l'enseignement
Bruno Kieffer : bruno.kieffer@unistra.fr

MCC

Les épreuves indiquées respectent et appliquent le règlement de votre formation, disponible dans l'onglet Documents de la description de la formation

Régime d'évaluation
CT (Contrôle terminal, mêlé de contrôle continu)
Coefficient
1.0

Évaluation initiale / Session principale - Épreuves

LibelléType d'évaluationNature de l'épreuveDurée (en minutes)Coefficient de l'épreuveNote éliminatoire de l'épreuveNote reportée en session 2
Data treatment and analysis
CTET1201.00

Seconde chance / Session de rattrapage - Épreuves

LibelléType d'évaluationNature de l'épreuveDurée (en minutes)Coefficient de l'épreuveNote éliminatoire de l'épreuve
Data treatment and analysis
CTET1201.00