This project aims to analyze the correlation and interdependence between the courses offered by the Federal University of ABC (UFABC) using a complex network-based approach. The project uses the igraph library for Python to calculate the PageRank and Closeness of the courses offered by UFABC.

The motivation behind this project is to provide a new perspective on the sequencing of the curriculum and to identify opportunities for improvement and development. The prolonged stay of students in the university and their unpreparedness are possible influencing factors that have led to the need for this analysis. The goal is to provide a roadmap to help students build a solid foundation for academic development and avoid possible disruptions in the progression of courses.

The project uses a complex network-based approach to calculate the PageRank and Closeness of the courses offered by UFABC. The first step is to collect data on the courses offered, their prerequisites, and the dependencies between them. The collected data is then used to create a network graph, where the courses are represented as nodes and the dependencies as edges. The PageRank and Closeness of each course are then calculated using the igraph library for Python.

This project was developed by a team of students from the Federal University of ABC:

Leonardo Trindade Fernandes Thiago de Souza Ferreira Kennedy Moises Brito Gouveia Vítor Misseno Feliciano da Silva Melissa Gomes de Oliveira