OVERVIEW

This teaching unit is structured into two modules: Operations Research (OR) and Machine Learning.
OR module introduces models and methods from Operational Research to provide students with tools to address decision-making problems. Students will learn linear programming techniques (including modeling, the simplex algorithm, sensitivity analysis, and duality theory) and integer programming. The module covers graph theory and network flow models-

AIMS AND CONTENT

LEARNING OUTCOMES

This teaching unit aims to provide students with knowledge of Operations Research models and methods and of Machine Learning methods applied to data, signal and image recognition. In the first case, the aim is to equip students with the tools to address decision-making problems. Specifically, students will learn linear programming techniques (including modeling, the simplex algorithm, sensitivity analysis, and duality theory) as well as integer programming (branch and bound, cutting planes). They will also learn to model decision-making problems in the telecommunications field using graph theory and network flow models. In the Machine Learning area, students will learn to characterize the distribution of a data set and reduce its dimensionality. They will be able to use various classification techniques, with or without training samples, optimizing their structure and parameters and evaluating their performance. They will be able to apply the learned methods to data sets of various types, including signals and images.

PREREQUISITES

Basic knowledge of mathematical analysis, geometry, and computer science.

TEACHERS AND EXAM BOARD

EXAMS

EXAM DESCRIPTION

The exam for the Operations Research module consists of a written test.

ASSESSMENT METHODS

The exam for the Operations Research module is based on a test that requires the students to solve exercises requiring the application of algorithms to the problem classes presented in the course, to answer to short theoretical questions, and to formulate simple combinatorial decision-making problems.