Study programme 2018-2019Français
Data Sciences IV: practice
Activité d'apprentissage à la Faculty of Science
CodeLecturer(s)Associate Lecturer(s)Subsitute Lecturer(s) et other(s)
  • GROSJEAN Philippe
      of instruction
      of assessment
      HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term

      Content of Learning Activity

      Good practices in experimental design, data and analyses organization in order to allow them to be shared (internally within the staff, or externally: Open Science). Statistical methods related to the Master Thesis's subject. Mastering of the dedicated software (R ecosystem).

      Required Learning Resources/Tools

      Not applicable

      Recommended Learning Resources/Tools

      Not applicable

      Other Recommended Reading

      Barnier, J., 2018. Introduction à R et au tidyverse ( Ismay, Ch. & Kim A.Y, 2018. Moderndive: An introduction to statistical and data science via R ( Wickham, H. & Grolemund, G, 2017. R for data science ( Zar, J.H., 2010. Biostatistical analysis (5th ed.). Pearson Education, London. 944pp. Dagnelie, P., 2007. Statistique théorique et appliquée, Volumes I et II (2ème ed.). De Boeck & Larcier, Bruxelles. 511pp (vol. I) 734pp (vol. II).

      Mode of delivery

      • Face to face
      • Mixed

      Type of Teaching Activity/Activities

      • Préparations, travaux, recherches d'information


      The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)

      (*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
      Date de génération : 02/05/2019
      20, place du Parc, B7000 Mons - Belgique
      Tél: +32 (0)65 373111