This teaching unit introduces students to the graph theory and operational research as modeling and decision-making tools for the data scientist. Therefore students will learn to make a mathematical and computer representation of graphs, apply the algorithms for traversing the graphs, calculate the shortest path, maximize a flow problem, analyse complex networks, use the Networkx Python library, use Markov chains to slove real-world problems, understand the Simplex algorithm and linear programming, use numerical tools for solving optimization problems.

Temps présentiel : 35 heures

Charge de travail étudiant : 70 heures

Méthode(s) d'évaluation : Examen final