Desenvolvimento de um Modelo de Inteligência Artificial com Scikit-Learn para Classificação de Atividades Complementares de Curso

Abstract

This work presents the development and evaluation of an artificial intelligence model for the automatic classification of Complementary Course Activity certificates. The approach employs supervised learning algorithms implemented in Python using the Scikit-learn library, evaluated on a pre-labeled corpus of certificates from the Bachelor’s degree program in Computer Science at IFFar/FW. The experiments indicate accuracy above 70% for all models, with the Neural Network achieving 82.54%, demonstrating the potential of the solution as a tool to support academic management.