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IESEG School of Management ( IÉSEG )

Code Cours :



Niveau Année de formation Période Langue d'enseignement 
MSc in Big Data Analytics for Business1S2English
Professeur(s) responsable(s)J.LIPENKOVA

Pré requis

Basic knowledge of programming concepts, preferably in R; basic concepts of statistics

Objectifs du cours

At the end of the course, the student should be able to:
Use basic concepts of text mining, such as text preprocessing, frequency distributions and classification, in applied settings

Contenu du cours

The course starts with a general presentation of text mining concepts, followed by a tutorial in which the students can apply the learnings. The second part of the course will be devoted to group projects focussing on real-world scenarios based on social network data. The projects will be prototyped during the course hours and finalised in personal work mode.

Modalités d'enseignement

Organisation du cours

TypeNombre d'heuresRemarques
Face to face
PBL class10,00  
Independent study
Group Project8,00  
Estimated personal workload26,00  
Charge de travail globale de l'étudiant50,00  

Méthodes pédagogiques

  • Tutorial
  • Presentation
  • Project work
  • Coaching


The final grade will be determined by the in-class participation of the students as well as by the quality of the group projects in which they will be participating in the second part of the course and as part of their personal work. Interim project status will be presented during the class; the presentation will also be included into the final grade.

Type de ContrôleDuréeNombrePondération
Continuous assessment
Group Project0,00160,00
TOTAL     100,00


  • Chris Manning and Hinrich Schütze, Foundations of Statistical Natural Language Processing, MIT Press. Cambridge, MA: May 1999. -

  • Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data, Springer, July 2011 -

Ressources internet

* Informations non contractuelles et pouvant être soumises à modification
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