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Master in Big Data Analytics

Graduate School of Engineering and Basic Sciences

Escuela de Ingeniería y Ciencias Básicas
Direction
Prof. Pedro Galeano San Miguel
Language
English
Attendance
On-campus
Credits
60 ECTS
Campus
Madrid - Puerta de Toledo
Applications

Closed

Departments
Statistics, Computer Science and Engineering Department , Telematic Engineering, Signal and Communications Theory, Mathematics, Research Institute UC3M-Santander of Financial Big Data (IFiBiD)

MORE INFORMATION HERE

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APPLICATION FOR ADMISSION

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  • Inicio

    Our Master program is oriented towards the training of people interested in working in data analytics, and in particular of analytics involving the evaluation of very large volumes of data in companies and organizations. Master’s students, either recently graduated or professionals, will receive both additional formation in the basic foundations of the analytics methods used for Big Data, and familiarity with their potential applications in different areas of interest.

    Particular emphasis will be placed on the use of applications based on analytic languages such as R and Python. The courses will also introduce data storage and processing paradigms such as MapReduce or noSQL, and their implementations (Hadoop, Storm, Spark, etc...), as well as cloud storing and computing methodologies. This knowledge will prepare them to handle large data sets and to conduct complex statistical and computational analysis of these data, to obtain results in pattern identification, prediction, forecasting, simulation or optimization, relevant for the improvement of the efficiency in the activities of companies and organizations.

    As an illustration of this potential demand, the French government expects that the needs for professionals with these qualifications during the coming five years on the whole of the EU will be in excess of 300,000 persons. In Spain, the use of these techniques is expected to increase by at least 300% in the next three years.

    BigData: sucesiones de bits construyendo un circuito interconectado

    reasons to study master in Big Data Analytics

     

    │MASTER IN NUMBERS

    • 40 students per class
    • ☛ International environment (more than 10 nationalities in class)
    • 100% of the students graduated in the Master received a job offer before completing the Master or few weeks later
    • ☛ It was the 1st official Master on the topic that received a positive evaluation from ANECA as designed in accordance with the European Higher Education Area (EHEA)
  • PROGRAM

    This Master program has been designed as a one academic year degree, offered in English and allowing for compatibility with other professional activities. The topics covered by the degree correspond to 60 ETCS credits, approximately equivalent to 400 hours of classes and 1100 hours of work from the students.

    It has been structured around 18 3-credit courses, offered during four 7-week periods. Five subjects are covered during each period, corresponding to 15 hours of class per week.

    A Master’s Thesis is required. It should provide the students with experience in the treatment of real data in a particular area of interest. It would be completed during the second half of the year.

    Course 1 - Annual

    Master's Thesis
    Subjects ECTS TYPE
    Master's Thesis 6 TFM

    C) Compulsory: 48 ECTS

    E) Elective Course: 6 ECTS

    TFM) Master's Thesis: 6


    For those students who consider making the Master part time in two academic years, it is recommended to follow one of the two options that can be found at the following link:

    Course directory

  • FACULTY

    UC3M FACULTY

    • ALER MUR, RICARDO
      Department of Computer Science and Engineering
      Associate Professor
      PhD
    • ARTÉS RODRÍGUEZ, ANTONIO
      Department of Signal Theory and Communications
      Full Professor
      PhD
    • AUSÍN OLIVERA, CONCEPCIÓN
      Department of Statistics
      Associate Professor
      PhD
    • BAGNULO BRAUN, MARCELO GABRIEL
      Department of Telematic Engineering
      Associate Professor
      PhD
    • CALDERÓN MATEOS, ALEJANDRO
      Department of Computer Science and Engineering
      Associate Professor
      PhD
    • CALLE GÓMEZ, FRANCISCO JAVIER
      Department of Computer Science and Engineering
      Associate Professor
      PhD
    • CARRETERO PÉREZ, JESÚS
      Department of Computer Science and Engineering
      Full Professor
      PhD
    • DÍAZ DE MARÍA, FERNANDO
      Department of Signal Theory and Communications
      Associate Professor
      PhD
    • FERNÁNDEZ MUÑOZ, JAVIER
      Department of Computer Science and Engineering
      Internal Associate Professor
      PhD
    • FUENTES GARCÍA-ROMERO DE TEJADA, JOSÉ MARÍA DE
      Department of Computer Science and Engineering
      Visiting Professor
      PhD
    • GALEANO SAN MIGUEL, PEDRO
      Department of Statistics
      Associate Professor
      PhD
    • GARCÍA BLAS, FRANCISCO JAVIER
      Department of Computer Science and Engineering
      Visiting Professor
      PhD
    • GARCÍA REINOSO, JAIME JOSÉ
      Department of Telematic Engineering
      Associate Professor
      PhD
    • GÓMEZ BERBIS, JUAN MIGUEL
      Department of Computer Science and Engineering
      Associate Professor
      PhD
    • HARITH TAHA ABDULLAH, ALJUMAILY
      Department of Computer Science and Engineering
      Visiting Professor
      PhD
    • MOLINA PERALTA, ISABEL
      Department of Statistics
      Associate Professor
      PhD
    • MORATO LARA, JORGE LUIS
      Department of Computer Science and Engineering
      Intern Associate Professor
      PhD
    • MORO, ESTEBAN
      Department of Mathematics
      Associate Professor
      PhD
    • NOGALES MARTÍN, FRANCISCO JAVIER
      Department of Statistics
      Associate Professor
      PhD
    • RUIZ MORA, CARLOS
      Department of Statistics
      Visiting Professor
      PhD
    • SÁNCHEZ, ÁNGEL
      Department of Mathematics
      Full Professor
      PhD
    • SÁNCHEZ FERNÁNDEZ, LUIS
      Department of Telematic Engineering
      Full Professor
      PhD
    • VALENCIA LÓPEZ, CARLOS
      Department of Telematic Engineering
      Postdoctoral researcher
      PhD
    • VEIGA, HELENA
      Department of Statistics
      Associate Professor
      PhD
    • VELILLA CERDÁN, SANTIAGO
      Department of Statistics
      Full Professor
      PhD
    • WIPER, MICHAEL PETER
      Department of Statistics
      Associate Professor
      PhD
  • ADMISSION

    Available places: 40

     

    Student profile

    The student who wants to pursue this Master must have good mathematical and statistical base, and a basic knowledge of programming. Likewise, should have sufficient ability to work with Web tools and an interest in real problems of processing data in different application areas .

    You must also have sufficient capacity for problem identification data processing in real environments , formalizing them and interpretation of the results obtained from the application of computational tools for this data processing.

    The interest in various aspects related to the management of companies and organizations will also be useful for the use of the teachings of the Master . Finally , creativity , imagination , innovation and motivation for continuous learning are characteristics with a significant contribution to the success in the use of lessons to be taught in this Master .

     

    Requirements

    The candidates should have a bachelor’s degree in any of the following areas:

    • Computer Science
    • Telecommunications Engineering
    • Statistics
    • Mathematics
    • Physics
    • Industrial Engineering

    Candidates with other backgrounds (like Business/Administration, Economics, Medicine or Health Sciences) could also be considered, but they should justify required levels of knowledge in the fields of Mathematics (Algebra and Calculus), Statistics (Probability and Inference) and Computer Science (basic programming skills). In any case, and depending on each particular case, the Master’s Academic Committee may recommend to students already admitted to carry out, prior to the beginning of the Master’s classes, one or more on line courses (MOOCs) about some of the previous contents.

    Professional experience is not required, but it will be considered as an asset within the admissions process.

    Admission Criteria

    The Master´s direction will evaluate the application based on the criteria described below, and informing to the student about the admission to the Master, motivated denial of admission or the inclusion in a list of provisional expected:

    • Academic record (40%)
    • Professional experience (20%)
    • Quantitative and computer science background of the student (10%)
    • Letters of recommendation submitted by the applicant (10%)
    • Others (10%)
    • English level (previous degree in english)

     

    Foreign students

    Once admitted to the Master, foreign students with university degree issued by a higher education institution belonging to an educational system outside the EEES, must present, for enrollment, the diploma attesting equivalent training that allows access to postgraduate studies, legalized by diplomatic procedures, or “The Hague Convention Apostille”. More information about Legalization of Documents.

    If needed, documents must be accompanied by an official sworn translation into Spanish.

     

    Admission

    The admission process will begin with the admission application, made through the online platform Carlos III University of Madrid, on the dates and periods approved and published for each academic year.

    • Curriculum vitae
    • Copy of academic title
    • Transcript
    • Cover letter and letter / s of recommendation
    • Another additional documents

     

    Application

    The request is made electronically through our application. Before starting the admission process it is important to consult the supporting information that we offer below:

  • SCHOOLARSHIPS

    UC3M Scholarships for the Year 2017/2018 *

    For the academic year 2016-17 has been published a call for a maximum of 8 grants for payment of the net enrollment rates for students accepted into the Master, with the following provision:

    • 8 grants of € 1,500

    Application deadline: 31st May 2017.

    Two possible resolutions: March and June 2017.


    The number of grants and amounts specified in the Annex to the notice, may vary depending on the conditions of the candidates who apply to them, can be even deserted as assessed by the Selection Committee for each program.


    » Financial aid/scholarships for tuition offered by School of Graduate Studies

    » Electronic Bulletin of the UC3M (BOEL)

     

    Call Carolina Scholarship Foundation Course 2017/2018

    The grant program of the Fundación Carolina offers 1 scholarship.

    Application Deadline: 6th April 2017.

    Fundación Carolina

    General Information about grants and scholarships

    You can find more information about scholarships of UC3M and other agencies or entities.

    Financial aid/scholarships for graduate programs

    Career Services

    University's Foundation (Fundación Universidad Carlos III) holds a careers service ( UC3M Guidance&Employment) which orientates, informs and helps graduates to get through the labour market.

  • PRACTICAL INFORMATION

    Enrollment

    Once you submit the application for admission, you will have to wait for the official acceptance in the Master program, before starting the enrollment process.

    Direct access general information enrollment and type Master

     

    Academic Calendar

    Academic Calendar 2016/17

    Academic Calendar 2017/18

     

    Time Schedule

    Direct access to timetable

    • Presentation of Master´s Thesis will be held in the months of June and July.
    • The classes for the Master program will take place from Monday to Friday from 4 p.m. to 7.15 p.m.

     

    Exam dates

    Direct access to exams schedule

     

    Program's Quality

    Quality of the Master's Degree

  • CAREER OPORTUNITIES

    Examples of some of the potential career opportunities associated to the successful completion of this Master program are:

    • Expert on information management within a large company, with responsibilities on the treatment of data for different areas such as clients and marketing, financial information or operational data, with the ability to propose actions based on the analysis of these (large scale) data.
    • Information manager in a company, responsible for the statistical analysis of the information present in large databases, and the development of models to support decision-making processes in the company.
    • Web data analyst. For companies with a significant Web presence, taking responsibilities in the evaluation of information collected from the Web, to detect patterns and to forecast outcomes that improve the presence of the company in its markets.
    • Marketing data analyst, working in the identification of trends in sales data, or the changes in spatial or temporal consumer patterns, to help define the marketing strategies of the firm.
    • Operations data analyst, detecting improvement opportunities in the processes within the company, through the reduction of costs and execution times, and the increase in the quality of their products and services.
    • External consultant, with the ability to offer solutions to companies for the treatment of their information, and the implementation of improvements based on the results of this treatment.
    • Systems developer, to implement the data analysis methods presented in the courses with the goal of providing simple results to support decision-making processes in the company.