| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) |
|---|---|---|---|
| I-MARO-156 |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 30 | 12 | 0 | 0 | 0 | Q2 |
Contents
data representation and analysis; factorial methods (principal components analysis, multiple correspondance methods, rank analysis, ...); regression, analysis of variance; classification, clustering, experimental design. Software : R, Weka
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
I. H. Witten, E. Frank. Data Mining : "Practical Machine Learning Tools and Techniques with Java Implementations". Morgan Kaufmann, 2010
J-M. Azaïs, J-M. Bardet, "Le Modèle Linéaire par l'exemple : Régression, Analyse de la Variance et Plans d'Expériences. Illustrations numériques avec les logiciels R, SAS et Splus", Dunot, 2006
R.E.Walpole, R.H.Myers, S.L.Myers, K.Ye, "Probability and Statistics for Engineers and Scientists", Prentice Hall, 2012
Mode of delivery
- Face to face
Term 1 Assessment - type
- N/A
Term 1 Assessment - comments
Not applicable
Term 2 Assessment - type
- Oral Examination
- Written examination
Term 2 Assessment - comments
Theoretical and practical questions with various difficulty levels.
Term 3 Assessment - type
- Oral examination
- Written examination
Term 3 Assessment - comments
Not applicable
Resit Assessment - Term 1 (B1BA1) - type
- N/A
Resit Assessment - Term 1 (B1BA1) - Comments
Not applicable
Type of Teaching Activity/Activities
- Cours (cours magistraux; conférences)
- Ateliers et projets encadrés au sein de l'établissement