Conception et réalisation d'un système de gestion et d'aide à la décision pour un établissement d'enseignement privé.

Abstract

New technologies have had a significant impact on businesses by transforming their way of communicating, working, managing data, and adapting to the economic environment. Companies have adopted these modern technologies to transform their classical management systems into more efficient decision-making systems. Artificial Intelligence, machine learning, as well as optimization and data analysis methods are some of the technologies that have transformed classical management systems of companies. Our project aims to develop a management system reinforced by decision-making functionalities for private educational institutions, using machine learning and optimization methods. hree key features are at the core of our work: student clustering, performance prediction, and route optimization for pickup. To design our solution, we have adopted a multiprocess development approach based on three processes from three different domains: UP, CRISP, and PGO. Clustering, classification, and optimization algorithms are at the heart of our application. The plementation of our system's functionalities relies on a variety of programming languages and development tools such as Laravel, Python, MySQL, as well as mapping APIs, and is reinforced by efficient operators to improve its performance and functionalities.