UE :Data Science for Big data – Science des données pour le Big Data
Responsable(s), établissement(s) | Michalis Vazirgiannis, Ecole Polytechnique Mauro Sozio – Telecom Paristech |
Adresse(s) mail | mvazirg@lix.polytechnique.fr sozio@telecom-paristech.fr |
Lieu principal d’enseignement | Ecole Polytechnique |
ECTS | 2.5 |
Nombre d’heures total | 21 |
Cours | 12 |
TD | 6 |
TP | 3 |
Objectifs |
To acquaint the students with algorithms, methods and techniques for the life cycle of a data science project i.e. the iterative and incremental approach to make sense of the data (structured, graph, text) around the following key components: Data engineering and Data analysis. This includes data pre-processing and cleaning, feature extraction and creation, supervised and non-supervised learning methods for potentially Big data. |
Prérequis | Data Bases, Algorithms, Probability/Statistics, Programming |
Syllabus |
Data engineering
Data analysis
Case Studies (from data mining cups or Kaggle) |
Language | English |