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Master of Lifelong Learning in Intelligent, Connected and Sustainable Mobility

  • Masters
  • Programs
  • Master of Lifelong Learning in Intelligent, Connected and Sustainable Mobility

School of Continuing Education

Imagen fichas Másteres Propios
Direction
Fernando Garcia ( Automatic Department)
Edición
2
Deputy Direction
Vicente Milanés (Renault)
Language
English
Attendance
Online
Credits
60
Duration
1 curso académico
Campus
Leganes
Applications

OPEN

Departments
Systems Engineering and Automation Department
Consult about the Master


* Required fields

  • Inicio

    The Master of Lifelong Learning in Intelligent, Connected and Sustainable Mobility is the first master's degree of its kind in Spain, which has the best professionals in the field of mobility at European level, in addition to the support of two renowned companies in the sector such as Renault and Eviden.

    This master's degree offers recently graduated engineers and professionals of the sector the tools for the development of a professional career in the field of mobility within the framework of the 21st century society. Learning relevant aspects such as connectivity technology, artificial intelligence, cybersecurity, computer vision, autonomous mobility ... All these technologies of great relevance in the industrial sector and with great applicability in mobility.

    Renault and Eviden logos
    Imagen Máster Movilidad Cooperativa, Conectada y Automatizada
  • PROGRAM

    Embedded Digital Systems (3 credits)
    Coordinator: Raúl Sánchez Reíllo (Electronics Technology Department)

    Students will learn about microcontrollers, hardware and software architectures, and programming techniques for embedded systems. Through practical projects and case studies, they will develop skills to create and optimize embedded digital systems that improve the functionality, safety, and efficiency of smart and connected vehicles.


    ADAS Systems and Sensors (3 credits)
    Coordinator: Fernando García (Automation Department)

    This course focuses on advanced driver assistance systems (ADAS) and the sensors that enable them. Students will explore technologies such as radar, lidar, cameras, and ultrasonic sensors, and how these are integrated into vehicles to improve safety and advance automated driving. Students will develop skills to design, implement, and evaluate innovative ADAS systems that contribute to safer and more efficient mobility.


    Connected Vehicles (6 credits)
    Coordinators: Juan Carlos Aguado Manzano (University of Valladolid) and José Eugenio Naranjo (Polytechnic University of Madrid)

    This course introduces students to communications technologies applied to mobility systems. Students will learn about communication networks, protocols, and standards for connected vehicles, as well as applications that improve safety, efficiency, and user experience. Students will develop skills to design and implement innovative solutions that integrate connectivity into the smart mobility ecosystem.


    Cybersecurity (6 credits)
    Coordinator: José María de Fuentes Garcia Romero de Tejada (Dept. of Computer Science)

    This course will allow students to acquire knowledge in the field of applied cybersecurity, developing skills to design and implement robust solutions that ensure the integrity, confidentiality, and availability of critical data and systems in urban mobility.


    Introduction to Machine Learning (3 credits)
    Coordinator: Álvaro García López (Eviden)

    This course aims to introduce students to highly topical topics in modern artificial intelligence, specifically those related to machine learning.

    This course is designed with a strong practical focus and seeks to acquire the basic knowledge that will allow students to develop mobility applications using machine language technologies.

     

    Big Data (3 credits)
    Coordinator: Esther Cid Romero (Eviden)

    This course seeks to delve deeper into the topic of Big Data and its applications in the field of mobility. It focuses on the analysis and management of large volumes of data to optimize transportation systems. Students will learn to use advanced data processing tools and techniques, predictive analytics, and visualization to extract valuable information that improves the efficiency, safety, and sustainability of mobility. Students will develop skills to implement Big Data-based solutions that transform the future of smart transportation.


    AI Applied to Mobility Services (3 credits)
    Coordinator: Fernando García (Automation Department)

    This course provides an in-depth understanding of how AI can revolutionize mobility services. Students will learn to apply machine learning algorithms and data analytics to solve traffic problems, improve the efficiency of transportation systems, and promote sustainable mobility, among other areas. Innovative solutions that are transforming urban mobility and smart transportation will be explored.


    Software Testing and Validation (6 credits)
    Coordinator: Antonio Amescua Seco (Dept. Computer Science)

    This course focuses on the methodologies and tools necessary to ensure software quality and reliability. Students will learn to design and execute rigorous tests, detect and correct errors, and validate application performance. Advanced techniques will be explored to ensure software robustness and security in mobility environments.


    Vehicle Dynamics (6 credits)
    Coordinator: Daniel Garcia-Pozuelo Ramos (Dept. Mechanics)

    This course focuses on the study of the forces and motions that affect vehicle behavior. Students will learn to analyze and model vehicle dynamics, including aspects such as stability, control, and traction. Through simulations, experiments, and practical projects, students will develop skills to design and optimize vehicles that are safe, efficient, and capable of delivering high performance under various conditions.


    Computer Vision (6 credits)
    Coordinator: Abdulla Al-Kaff (Automation Department)

    This course offers an in-depth exploration of the techniques and applications of image processing and visual analysis. Students will learn to develop and implement advanced algorithms for object detection and recognition, video analysis, and scene understanding. Through practical projects, students will acquire skills for application in various fields, with particular emphasis on mobility use cases.


    Smart and Connected Vehicle Architecture (3 credits)
    Coordinator: Jorge Villagrá (CSIC)

    This course addresses the design and development of advanced vehicles equipped with connectivity and artificial intelligence technologies. Students will explore the integration of sensors, communication systems, and data processing platforms to create autonomous and connected vehicles. Through case studies and practical projects, students will gain insight into how these technologies transform mobility, improve safety, and optimize transportation efficiency.


    Master's Thesis (12 credits)
     

  • FACULTY

    UC3M Faculty

    • Abdulla Al Kaff
      Systems and Automation Engineering
      Assistant Professor
    • Fernando García Fernández
      Systems and Automation Engineering
      Full Professor
    • José María de Fuentes García Romero de Tejada
      Computer Science
      Full Professor
    • Lorena González Manzano
      Computer Science
      Full Professor
    • Antonio Amescua Seco
      Computer Science
      Professor
    • Daniel García-Pozuelo Ramos
      Mechanical Engineering
      Full Professor
    • Marñiaa Jesús López Boada
      Mechanical Engineering
      Professor
    • Beatriz López Boada
      Mechanical Engineering
      Professor

     

    External Faculty

    • Vicente Milanés
      Renault
      Innovation Project Manager
    • José Eugenio Naranjo Hernández
      Polytechnic University of Madrid Madrid
      Department of Computer Systems Engineering
      University Professor
    • Felipe Jiménez Alonso
      Polytechnic University of Madrid
      Department of Mechanical Engineering
      University Professor
    • Juan Carlos Aguado Manzano
      University of Valladolid
      Signal Theory and Communications
      Full Professor
    • Jorge Villagrá
      CSIC
      Terminated Scientist
    • Jorge Godoy
      CSIC
      Terminated Scientist
    • Esther Cid Romero
      Eviden
      Industry Leader
    • Alvaro García López
      Eviden
      Business Development Architect
    • Irene Cortes Lafuente
      Renault
      SW Project Manager
    • Carlos Guindel Gómez
      Renault
      ADAS/AD Software Engineer
  • ADMISSION
    • ADMISSION

      Number of Available Places: 40

      The program will be offered provided that there is a minimum number of students to ensure its viability.


      Required Qualifications

      The entry profile for this master's degree must be postgraduate students who have completed a degree in STEM subjects (Science, Technology, Engineering, and Mathematics). However, due to the distinctly multidisciplinary and integrative nature of the master's degree, the program committee reserves the right to grant access to other profiles whose prior knowledge, while not included in those described above, guarantees the achievement of the training objectives. For these profiles, the Master's Admissions Committee will determine the necessary additional training options based on each applicant's prior training.


      Student Profile

      Given that the Master's program focuses on cross-disciplinary technologies, its program is designed for:

      • Students with degrees in Industrial Engineering, Telecommunications Engineering, and Computer Engineering who wish to focus their professional careers on the mobility sector.
      • Professionals related to the mobility sector in general who need to update their knowledge in order to implement the latest technologies in the sector.


      Selection and evaluation criteria

      The suitability and ranking of candidates will be based on the following admission criteria:

      • Academic record for admission studies (Maximum 80)
      • English proficiency level above B2 (Maximum 10)
      • Other merits (Maximum 10)
      • From the academic record for the degree that qualifies for admission, the following will be taken into account: the average grade, the number of years required to obtain the degree, and the suitability of the study program followed for the master's program.
      • Other merits include: other academic studies, professional experience in the field of mobility, scholarships and awards received, motivation letter, letters of recommendation, language skills, etc.


      Language Requirements:

      As this is a master's degree taught in English, the generic criteria required at UC3M will be followed: "This knowledge can be accredited with an official English qualification, at least level B2, which includes assessments in the four areas: listening, reading, speaking, and writing, such as the TOEFL, IELTS, or Cambridge ESOL exams.

      As a general rule, the following minimum scores are required:

      • TOEFL (iBT): 72 - 94
      • IELTS: 5.5 - 6.5
      • Cambridge ESOL: English Language Certificate (FCE)
      • Linguaskill: 160 - 179
      • Common European Framework (Languages): Level B2
      • Aptis: Level B2

      The language requirements will not be required for students whose native language is English or for those who have completed their entire university studies in English, upon presentation of the corresponding documentation.

       

       

       

      Admission Process

      • Application form

      • Academic transcript (grades obtained during the program)

        Copy of academic degree, if applicable

        Photocopy of ID or Passport

        Language Certificate

        If you have not completed your studies: Compromiso de finalización


      Admission Application

      The application is submitted electronically through our application.

      Steps to follow to submit your admission application


      Contact:

      Postgraduate Center

      School of Continuing Education

      mastermovilidad@postgrado.uc3m.es

       

    • ENROLLMENT

      El importe de la matrícula es de 6.000 €

      El pago de la matrícula del programa se podrá fraccionar en varios plazos distribuidos de la siguiente manera:

      • el primer plazo, una vez que se haya notificado por escrito su admisión, deberá ingresar la cantidad de 1.000€, como pago del primer plazo y reserva de plaza.
      • el segundo plazo, por importe de 2500 €, antes del 31 de octubre
      • el tercer plazo, por importe de 2500 €, antes del 15 de marzo

      Sólo se podrá solicitar la devolución de los derechos de reserva de plaza, en el supuesto de imposibilidad de asistencia por causa de enfermedad grave justificada u otro motivo sobrevenido de equiparable gravedad, así como por causa de fuerza mayor.

  • PROFESSIONAL OPPORTUNITIES

    Graduates will be able to carry out a process of analysis and synthesis to solve problems, design, and evaluate solutions in the field of mobility based on a thorough understanding of current regulations and the fundamentals of the technologies involved, such as sensors, on-board electrical and electronic systems, artificial intelligence, and cybersecurity.

    In addition, they will be competent to carry out designs in the field of intelligent vehicles and autonomous mobility, on-board systems, business projects in the field of mobility, cybersecurity applied to mobility, and artificial intelligence, which meet the required specifications, collaborating with other professionals in related technologies within multidisciplinary teams.

    Finally, graduates will be competent to apply their knowledge and understanding to solve problems and design devices, equipment, processes, or procedures in the field of mobility, according to criteria of cost, quality, safety, efficiency, and respect for the environment. It should be noted that this degree provides the generic skills that graduates require to practice engineering in today's society: communicating knowledge orally and in writing, to both specialized and non-specialized audiences, working in multidisciplinary and international teams, continuous learning that allows them to adapt to new situations, etc.

    All these skills and abilities will allow them to enter a thriving job market, which seeks to apply the latest technologies in communications, electronics, and artificial intelligence in the field of mobility.

  • PRACTICAL INFORMATION

    Duration and Schedule

    The courses will be divided into two-hour time slots (two 45-minute sessions with 15-minute breaks). The afternoon classes will be held Monday through Friday, from 5:00 p.m. to 9:00 p.m. Fridays will be reserved for make-up sessions and seminars.


    Additional Information

    a) The email address provided by the University to the student upon registration will be used primarily for communications with the student, so it is essential to activate it and check it regularly.

    b) Failure to pay by the established date will result in the denial or cancellation of registration under the terms and conditions established by the University.

    Location

    ☛ Leganés Campus

    ☛ Take a virtual tour of the Leganés Campus

    ☛ More information about the Campus

     

    Visita Virtual Leganés
  • AIDS

    El máster se ha preparado junto a un programa de becas y prácticas en empresa, que incluyen a las empresas promotoras, para que los estudiantes puedan coger experiencia en una empresa puntera en el sector.

    Los estudiantes del programa podrán optar a este programa durante el transcurso del máster.