Résumé: With the exponential growth in generated data and the great value it holds, analyzing it to extract meaningful insights and base important decisions on them has become a necessity, especially for companies as it is now crucial for their success. Customers churn is one of the most common and costly issues with telecom companies, one way to address this issue is to predict new customers’ decision by analyzing old one’s data in order to understand why they chose to churn and on what metrics they based this decision and then react upon the results. The aim of this end-of-study project was to use data analytics tools to understand and analyze data provided by a telecom company with a moderately high churn rate and also to put in use Machine Learning models and choose suitable ones to deploy in a Web application that predicts customers’ decisions

Encadrant: MAJDA A.

Jurry: Pr. Aicha MAJDA Pr. Mohamed OUZARF Pr. Abdelali BOUSHABA

Lieu de Stage: Laboratoire Systèmes Intelligents et Applications FST FES.