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UPV
 

Master's Degree in Computer and Network Engineering Vera (València) Campus, Universitat Politècnica de València

Master's Degree in Computer and Network Engineering

60 credits

Credit 35,34 €
(2024/2025)

23 openings
(2024/2025)

Introduction

Modern computer systems are made up of several computing components that are interconnected at all levels, whether they be big servers supporting cloud services or distributed computing systems that comprise the edge and interact with the outside world via sensors and actuators, forming what has come to be known as the Internet of Things (IoT).

We are currently witnessing dramatic growth in connectivity, the size of systems and the number of devices connected to the internet. The amount of data that has to be processed is growing rapidly, and it has to be obtained from heterogeneous and, often, widely scattered sources. Networked systems are becoming increasingly widespread in all areas of socioeconomic activity, e.g. industry, communications, the automotive industry, transport, logistics, agriculture, health, leisure and culture, etc. Computer systems connected to the internet.

This digital revolution will be led by professionals, engineers and scientists who are highly specialised in the field of networked computer systems and able to provide effective solutions to the problems inherent in these systems, such as performance, scalability, energy efficiency, reliability and security

The Master's Degree in Computer and Network Engineering is aimed at training specialised professionals and researchers with international competence in the area of networked computer systems and computing devices, covering areas ranging from cloud computing to edge computing.

To this end, the Master's Degree provides an in-depth study of mobile network-based systems, wireless sensor and actuator networks, networks for control applications, embedded and distributed systems, computer cluster configuration and administration, heterogeneous architectures for number crunching, the architecture and features of modern multi-core processors, the IoT, the security and reliability of networked computer systems, adaptability and reconfiguration in fault-tolerant solutions, cyber security, and the processing and transmission of multimedia information.

This video video presents some opinions of former students of the master's degree.

Objetivos

To train professionals and researchers who are capable of:

Designing, configuring, sizing and optimising computer systems, including computing infrastructures, interconnection technologies, sensing and actuating devices, and system software (middleware).

Learning about technologies used to collect, transmit and process big data obtained from very diverse sources.

Helping to improve the performance, scalability, energy efficiency, reliability, fault tolerance and security of computing systems that have to process large amounts of data, and the networks that interconnect those systems at both cloud and edge level.

Designing and analysing IoT architectures, and developing IoT services and applications for different areas, e.g. smart cities, autonomous vehicles, intelligent transport systems, smart homes, eHealth, smart agriculture and industry 4.0.

Configuring, sizing, optimising and administrating large data centres for efficient support of HPC applications, cloud services, social networks, e-commerce servers, web servers, banking transactions, multimedia applications, etc.

Transferring technology to businesses in the sector and/or research centres

Leading and collaborating with other professionals and researchers in the field of knowledge of the Master's Degree.

Contributing to scientific, technical, social and economic progress, within the framework of the industries and institutions where they carry out their professional work.

Admission criteria

The Academic Committee of the Master's Degree will analyse the applications and decide whether the candidates meet the academic requirements for admission to the master's degree. This Committee will establish a scale, based mainly on the academic record of the applicants and the affinity of their previous studies with the content of the master's degree, which will be used to select the candidates

Organisation

Department of Computing Engineering

Cofinancing

Ministry of Education

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