This course introduces students to distributed computing paradigms and big data processing techniques. It focuses on data parallel processing using MapReduce and Apache Spark. Students will gain hands-on experience in managing and analyzing large-scale datasets in distributed environments.

Temps présentiel : 37.5 heures

Charge de travail étudiant : 100 heures

Méthode(s) d'évaluation : Projets