Dual Bachelor in Data Science and Engineering and Telecommunication Technologies Engineering

• Program modified in 2025. In 2025/26 will be offered 1st year.

• Field of knowledge in the Bachelor's Degree in Telecommunications Engineering: Electrical engineering, electronic engineering and telecommunications engineering.
• Field of knowledge in the Bachelor's Degree in Data Science and Engineering: Electrical engineering, electronic engineering and telecommunications engineering.

 

 

 

 

Study plan for students who started in the academic year 2024/2025 or earlier.

• In 2025/26 only 2nd, 3rd, 4th and 5th. year will be offered.

 

 

 

 

Exchange programs

The Erasmus programme permits UC3M first degree and post graduate students to spend one or several terms at one of the European universities with which UC3M has special agreements or take up an Erasmus Placement, that is a work placement or internship at an EU company. These exchanges are funded with Erasmus Grants which are provided by the EU and the Spanish Ministry of Education.

The non-european mobility program enables UC3M degree students to study one or several terms in one of the international universities with which the university has special agreements. It also has funding from the Banco Santander and the UC3M.

These places are offered in a public competition and are awarded to students with the best academic record and who have passed the language threshold  (English, French, German etc..) requested by the university of destination.

Movilidad Europea

Listof European universities with mobility agreements:

Movilidad No Europea

List of non-European universities with mobility agreements:

Entry profile

It is highly recommended that the student who enters this Degree has completed the Baccalaureate of Science (or, if applicable, an equivalent Baccalaureate or similar in terms of the subjects taken when the student comes from other non-Spanish educational systems). Advanced knowledge in areas such as mathematics, physics, computer science and statistics will be required.

Along with students of Baccalaureate, the other main group of access to the Degrees is that of Vocational Training students. Of all the Higher Level Training Cycles and professional families, for this degree, those belonging to the following are presented as the most recommendable in the entry profile:

Professional family of Computer Science and Communications, especially the training cycles of Higher Technician in Administration of Computer Systems in network, development of multiplatform applications and development of web applications.

In order to highlight some suitable competence content in relation to the entry profile, the student should have a good previous training in Mathematics. Personal attitudes of initiative, teamwork, personal organization of work, capacity for abstraction, critical thinking and responsibility and interest in the practical application of knowledge to solve real problems as well as a high level of competence in management skills and technology management are highly valued.

Access routes and application for a place in the degree program

Graduation Profile

Graduates of the Dual Degree in Data Science and Engineering and Telecommunication Technologies Engineering will have extensive knowledge and understanding of the basic general fundamentals of engineering, as well as in particular, those of telecommunication technologies and data engineering.

They will be able to prepare big data infrastructures for further analysis, to design and build systems capable of integrating data from various resources and to manage large volumes of data in order to optimize the performance of the data ecosystem of a company, organization or entity. In addition, graduates will be able to convert raw data into knowledge by applying statistical, machine learning and pattern recognition techniques to solve critical business problems. To this end, graduates will have strong programming skills, the ability to design new algorithms, handle large volumes of data, and the analytical skills to interpret the results of their findings and display them through visualization techniques. In addition, graduates will need to be up to date with the latest state-of-the-art computing technologies, as they will need to work with data sets of different sizes and shapes and be able to run their algorithms on big data effectively and efficiently.

They will also be able to carry out an analysis process to solve telecommunication systems problems, and will be competent to perform engineering designs in their field, working in a team. Graduates will also be able to carry out research and make innovative contributions in telecommunication technologies, which justifies the scientific interest of this degree. Finally, graduates will be competent to apply their knowledge to solve problems and design telecommunication devices, knowing the environmental, commercial and industrial implications of engineering practice in accordance with professional ethics; this is of vital importance for the professional interest of the degree.

1. Knowledge of Titles

K1 - To know the principles and values of democracy and sustainable development, in particular, respect for human rights and fundamental rights, gender equality and non-discrimination, the principles of universal accessibility and climate change, in line with their professional development in the field of the degree.

K2 - To know basic humanistic contents, oral and written expression, following ethical principles and completing a multidisciplinary training profile.

K3 - To know fundamental contents in their area of study starting from the basis of general secondary education and reaching a level proper of advanced textbooks, including also some aspects of the forefront of their field of study.

K4 - Knowledge of basic scientific and technical subjects that qualify for the learning of new methods and technologies, as well as providing a great versatility to adapt to new situations, in the field of data storage, management and processing.

K5 - Ability to understand and relate fundamental concepts of probability and statistics and be able to represent and manipulate data to extract meaningful information from them.

K6 - Acquire the fundamentals of Bayesian Statistics and learn the different techniques of intensive computing to implement Bayesian inference and prediction, applying them to data analysis, uncertainty modeling, and decision-making in real-world problems in Data Science and Engineering.

K7 - Assimilate basic concepts of programming, including control structures, data types, and functions, and their application in developing programs for data analysis, processing, and visualization in the field of Data Science and Engineering.

K8 - Differentiate data structures, algorithms, databases and files oriented to data processing.

K9 - To know the theory of languages, grammars and automata and their application to lexical and syntactic analysis associated with data analysis.

K10 - To know and manage the fundamentals of analog and digital signal processing in the time and frequency domains, including sampling, filtering and transforms, with applications to signal processing in the field of Data Science and Engineering.

K11 - Understand the modeling, prediction, filtering and smoothing of random signals and stochastic processes, with applications in time series analysis, pattern detection, and optimization of models in Data Science and Engineering.

K12 - Know and understand the fundamentals of network architectures, security requirements (with an emphasis on privacy) of big data environments and the consequent protection measures: technical; organizational and legal, as well as to know and handle encryption techniques and their use to guarantee data security.

K13 - To know and identify basic and current aspects of the functional areas of the company and understand the relationship between them to promote entrepreneurship, in the development and implementation of systems in the field of data science and engineering.

2. Skills of Titles

S1 - To plan and organize team work making the right decisions based on available information and gathering data in digital environments.

S2 - To use information interpreting relevant data avoiding plagiarism, and in accordance with the academic and professional conventions of the area of study, being able to assess the reliability and quality of such information.

S3 - Ability to solve technological, computer, mathematical and statistical problems that may arise in data engineering and science, applying knowledge of mathematics, probability and statistics, programming, databases, and languages, grammars and automata.

S4 - Ability to solve mathematically formulated problems applied to various subjects, using numerical algorithms and computational techniques, and applying knowledge of: algebra; geometry; differential and integral calculus; numerical methods; numerical algorithms; statistics and optimization.

S5 - Ability to correctly identify predictive problems corresponding to certain objectives and data, based on knowledge of algorithms, modeling, prediction and filtering, and to use the basic results of regression analysis as the basis for prediction methods.

S6 - Ability to correctly identify classification problems corresponding to certain objectives and data, based on knowledge of algorithms, modeling, prediction and filtering, and to use the basic results of multivariate analysis as the basis for classification, clustering and dimension reduction methods.

S7 - Capability for mathematical modeling, algorithmic implementation and optimization problem solving related to data science, relying on knowledge of mathematics, algorithms, programming and optimization.

S8 - Ability to use the main technologies used for processing large amounts of data, taking into account the knowledge of security and protection measures in these environments.

S9 - Apply, design, develop, critically analyze and evaluate machine learning methods in classification, regression and clustering problems and for supervised, unsupervised and reinforcement learning tasks.

S10 - Apply, design, develop, critically analyze and evaluate solutions based on artificial neural networks.

S11 - Apply, design, develop, critically analyze and evaluate solutions based on machine learning for applications in specific domains such as recommendation systems, natural language processing, Web or social networks.

S12 - Apply, design, develop, critically analyze and evaluate image and video processing, and computer vision solutions.

S13 - Apply fundamental knowledge of network architectures.

S14 - Apply, design and develop Web and applications and use them to capture data.

S15 - Apply, combine,design and develop data visualization tools to communicate the results of data analysis, adapting them to different audiences, both technical and non-technical.

S16 - Ability to synthesize the conclusions obtained from the analyses carried out and present them clearly and convincingly both in writing and orally to both specialized and non-specialized audiences.

3. Competences of Titles

C1 - To Know and be able to handle interpersonal skills on initiative, responsibility, conflict resolution, negotiation, etc., required in the professional environment.

C2 - To develop those learning skills necessary to undertake further studies with a high degree of autonomy.

C3 - Ability to solve problems with initiative, decision making, creativity, and to communicate and transmit knowledge, skills and abilities, understanding the ethical, social and professional responsibility of the data processing activity. Leadership capacity, innovation and entrepreneurial spirit.

C4 - Teamwork in international and interdisciplinary contexts.

C5 - Be able to analyze and synthesize basic problems related to engineering and data science, elaborate, defend and efficiently communicate solutions individually and professionally, applying the knowledge, skills, tools and strategies acquired or developed in their area of study.

C6 - To present and defend, individually and before a university panel a project in the area of the specific technologies of Data Science and Engineering, being of a professional nature, which synthesizes and encompasses the competences acquired in the degree program.

C7 - To apply and adapt technical knowledge and practical skills in the field of Data Science and Engineering, participating in problem-solving and the development of solutions in a professional environment.

1. Knowledge of Titles

K1-FT - To know the principles and values of democracy and sustainable development, in particular, respect for human rights and fundamental rights, gender equality and non-discrimination, the principles of universal accessibility and climate change.

K2-FT - To know basic humanistic contents, oral and written expression, following ethical principles and completing a multidisciplinary training profile.

K3-FB11 - Basic concepts of computer use and programming, operating systems, databases and IT programs with engineering applications.

K4-FB12 - Understanding and command of the basic concepts of the general laws of mechanics, thermodynamics, electromagnetic fields and waves, and their application to resolve problems characteristic of engineering

K5-FB13 - Understanding and command of basic concepts of linear systems and related functions and transformers. Electrical circuit theory, electronic circuits, physical principles of semiconductors and logic families, electronic and photonic devices, materials technology and their application in resolving problems characteristic of engineering.

K6-FB14 - Requisite knowledge of the concept of business, and the institutional and legal framework of a business. Business organization and management.

K7-ECRT14 - Knowledge of methods of network and routing interconnection as well as the fundamentals of network planning and sizing based on traffic parameters.

K8-ECRT15 - Knowledge of telecommunications legislation and regulations at the national, European and international levels.

KOPT-1 - To know and understand in depth advanced technologies in the specific field of engineering and information and communication technologies, which constitute the state of the art in the area of study, including emerging trends and recent developments.

KOPT-2 - To interpret sources of scientific and technical information in order to deepen the knowledge of a specific area related to engineering and information and communication technologies.

2. Skills of Titles

S1-FT - To plan and organize team work making the right decisions based on available information and gathering data in digital environments.

S2-FT - To use information interpreting relevant data avoiding plagiarism, and in accordance with the academic and professional conventions of the area of study, being able to assess the reliability and quality of such information.

S3-FB10 - Ability to solve mathematical problems arising in engineering. Aptitude for applied knowledge in: linear algebra, geometry; differential geometry; differential and integral calculus; differential equations and partial derivatives; numerical methods; numerical algorithms; statistics and optimization.

S4-ECRT7 - Knowledge and use of the fundamentals of programming in telecommunication networks, systems and services.

S5-ECRT10 - Knowledge and application of the fundamentals of hardware description languages.

S6-ECRT12 - Knowledge and use of the concepts of network architecture, protocols and communications interfaces.

SOPT-1 - Identify, assess their technical feasibility and apply advanced technological tools, methodologies and solutions used in the field of engineering and information and communication technologies to develop algorithms or systems integrating innovative and cutting-edge technologies.

SOPT-2 - Apply analytical and design methodologies to solve advanced problems in the field of engineering and information and communication technologies, and evaluate the performance and limitations of different technological approaches, proposing improvements and alternatives.

3. Competences of Titles

C1-FT - To Know and be able to handle interpersonal skills on initiative, responsibility, conflict resolution, negotiation, etc., required in the professional environment.

C2-ECRT1 - Ability to learn and acquire autonomously the requisite new knowledge for the design, development and utilization of telecommunication systems and services.

C3-ECRT2 - Ability to use communication and IT applications (office technology, databases, advanced calculus, project management, project visualization, etc.) to support development and utilization of electronic and telecommunication networks, services and applications.

C4-ECRT3 - Ability to use IT search tools for bibliographic resources and information related to electronic and telecommunications.

C5-ECRT4 - Ability to analyze and specify the fundamental parameters for a communications system.

C6-ECRT5 - Ability to weigh the advantages and disadvantages of different alternative technologies for development and implementation of communication systems, from the point of view of signal space, perturbations and noise, and analog and digital modulation systems.

C7-ECRT6 - Ability to conceive, develop, organize and manage telecommunication networks, systems, services and infrastructures in residential (home, city, digital communities), business and institutional contexts, responsibility for set up, continuous improvement, together with knowledge of social and economic impact.

C8-ECRT8 - Ability to understand the mechanisms of electromagnetic and acoustic wave propagation and transmission, and their corresponding transmitting and receiving devices.

C9-ECRT9 - Ability to analyze and design combinational and sequential circuits, synchronous and asynchronous circuits and use of microprocessors and integrated circuits.

C10-ECRT11 - Ability to use different sources of energy and in particular, solar photovoltaic and thermal energy, as well as the fundamentals of electro-technics and power electronics

C11-ECRT13 - Ability to differentiate the concepts of network access and transport, circuit switching and packet switching networks, fixed and mobile networks as well as systems and applications of distributed networks, voice services, audio, data, video and interactive services and multimedia.

C12-ETEGITT1 - Ability to construct, use and manage telecommunication networks, services, processes and applications, such as systems for capture, transport, representation, processing, storage, and multimedia information presentation and management, from the point of view of transmission systems.

C13-ETEGITT2 - Ability to select circuits, radiofrequency, microwave, radio broadcasting, radio-links and radio determination subsystems and systems.

C14-ETEGITT3 - Ability to analyze, codify, process and transmit multimedia information using analog and digital signal processing techniques.

C15-ETEGITT4 - Ability to construct, develop and manage telecommunication networks, services, processes and applications, such as capture, transport, representation, processing, storage, and multimedia information presentation and management systems, from the point of view of telematics services.

C16-ETEGITT5 - Capacity to apply techniques on which telematics networks, services and applications are based. These include systems for management, signaling and switching, routing, security (cryptographic protocols, tunneling, firewalls, payment authentication mechanisms, and content protection),traffic engineering(graph theory, queuing theory and tele-traffic), tarification and service reliability and quality, in fixed, mobile, personal, local or long distance environments, with different bandwidths, including by telephone and data.

C17-ETEGITT6 - Ability to design network architectures and telematics services.

C18-ETEGITT7 - Ability to program network and distributed telematics services applications.

C19-ETEGITT8 - Ability to construct, develop and manage telecommunication systems applications, such as systems for capture, analog and digital processing, codification, transport, representation, processing, storage, reproduction, management and presentation of audiovisual services and multimedia information.

C20-ETEGITT9 - Ability to create, codify, manage, disseminate and distribute multimedia content, in accordance with criteria of usability, accessibility of audiovisual services, diffusion and interactivity.

C21-ETEGITT10 - Ability to select specialized electronic circuits and devices for the transmission, routing, and terminals, in fixed as well as mobile environments.

C22-ETEGITT11 - Ability to design analog and digital electronic circuits, analog-digital and digital-analog converter circuits, radiofrequency circuits, and electrical power converter circuits for telecommunication and computational applications. 

C23-ETETFGITT1 - It will consist of a project in the area of the specific technologies of Telecommunications Engineering, being of a professional nature, which synthesizes and encompasses the competences acquired in the degree program.

C24-PAE - To apply and adapt technical knowledge and practical skills in the field of telecommunication engineering, participating in problem-solving and the development of solutions in a professional environment.

COPT-1 - To conceive and develop projects that integrate advanced knowledge and provide innovative solutions in the field of engineering and information and communication technologies.

External internships

External Internships for the Degree in Telecommunication Technologies:

• Telefónica I+D
• Everis España S.L.U.
• Ericsson España S.A.
• Amazon Spain Services S.L.
• Airbus Defence and Space S.A.U.
• Orange Espagne S.A.U.
• Santander Securities Services S.A.U.
• Altran Innovación S.L.
• IS2 Global Telecom Solutions S.L.U.
• ionIDe Telematics S.L.
• Sistemas Avanzados de Tecnología (SATEC)
• Ocaso S.A.
• INDRA Sistemas S.A.
• GMS Management Solutions S.L.
• One eSecurity S.L.
• Avaatel Telecom S.L.
• Evolutio Cloud Enabler S.A.U.
• Accenture S.L.

Career opportunities

Graduates of this double degree have before them a very wide range of employment opportunities: on the one hand, the demand for personnel in the field of artificial intelligence is and will be much higher than the supply; on the other, although this imbalance in favor of demand has always existed in the field of telecommunications, it is becoming even more acute in a labor market that increasingly demands digitalization, connectivity (in health, transportation, labor, energy, industry, finance, etc.), cloud services and cybersecurity.

There are many strategic sectors in which a strong demand for this type of training is expected: high-tech and communications, media and entertainment, automotive and assembly, basic resources and services, transportation and logistics, healthcare, biosciences, professional services, retail, education, marketing, customer and supplier relations, and the public sector.

As a consequence of the above, both the data scientist and the telecommunications technology graduate have many and varied employment opportunities, for example:

• Data Scientist (generalist designation encompassing data management, design and development of artificial intelligence algorithms in any sector).
• Data Engineer (generalist designation that provides hardware and software support to Data Science)
• Communications network engineer
• Advanced telecommunications services engineer
• Telecommunications product support engineer
• Telecommunications equipment engineer (design, maintenance, repair)
• Cloud support engineer
• Communications services manager in the public or private sector
• Telecom product after-sales engineer
• Telecom product sales engineer
• Telecommunications consultancy
• Consulting in the field of artificial intelligence
• Software developer (software engineering in the field of artificial intelligence or telecommunications)
• Web/mobile application developer (data capture, storage, management and visualization)
• Intelligent services designer and developer
• Strategy Engineer (alignment of the organization's strategy with the required technology)
• Data Analytics Manager
• Director of Digital Research and Development
• Digital Business Director
• Digital Business Development Manager
• Director of Digital Innovation, Digital Product
• Digital Marketing Director
• Digital Business Consultant
• Executive Director
• Digital Transformation Director
• Digital Sales Director
• Digital Operations Director

Schedules and calendars

Schedule in Dual Bachelor in Data Science and Engineering and Telecommunication Technologies Engineering

Academic calendar

Exams calendar (first semester)

Exams calendar (second semester)

Exams calendar (recovery tests)

Schedules and calendars

Schedule in Dual Bachelor in Data Science and Engineering and Telecommunication Technologies Engineering

Academic calendar

Exams calendar (first semester)

Exams calendar (second semester)

Exams calendar (recovery tests)