Business Intelligence and Big Data in Cyber-Secure Environments


Click for listings

    Official master Interuniversity Programme of 60 credits (51 in compulsory subjects + 9 of master thesis), distributed in two semesters. Limited places: 27 students.

    Type teaching non-classroom or online, based on continuous evaluation and projects.

    Specialized in the fields of higher growth and economic and social relevance today, as it is the analysis and processing large amounts of data (Big Data) heterogeneous, with the aim of extracting information that supports, facilitate and streamline the taking of decisions in the world business and/or social.

    To make that possible is essential to ensure the security both in storage and in transmission of those data. Increasingly important aspect today, is this relevant in these studies with a module of 15 centered credits in the Security of data and the Cybersecurity, which also addresses the related legal aspects. This module is one of the differential characteristics of our Master.

    Professional highly qualified they are only achieved through a quality teaching. This is our proposal, quality training, based on a firm theoretical basis, but with a practical approach in all studied. For this purpose we have university professors with accredited experience teaching and research of the University of Burgos, Leon and Valladolid, as well as with professionals in the field of Big Data, Business Intelligence and security. We also have the guarantee of quality of being one certified studies by official evaluation agencies.

    The graduates they will be capable of develop and direct projects in large volumes of data, and apply them to business and decision making, and all this, with about both legal and technical knowledge in relation to security and cybersecurity.

    Before Enrolling

    If you're interested in these studies, there are three very important things to keep in mind before you enroll:

    1. Charging

      It is a Master's degree in 60 ECTS, delivered in a school period, excluding the one dedicated to the End of Master's Work (9 credits), of 32 weeks. Each ECTS is a workload of 25 hours. Therefore, the weekly workload of this master's degree is about 40 hours per week, about.

      Before you enroll it is important that you value your weekly time availability. There's always the option of part-time enrolment.

    2. Necessary prior knowledge

      For the correct use of studies, the minimum prior knowledge that the student must have is:

        • General experience in the field of computing. You must have knowledge of managing a computer both at the user level and in basic team management. Data sets will be accessed and managed, therefore, the student must have basic knowledge in the field of SQL databases.
        • It's going to take some basic knowledge of UNIX Shell commands. In the following link CeroShellUnix Course you can find a basic tutorial.
        • Knowledge in software development. No big software projects are going to be done, but you do need to know how to program. It is necessary to know object-oriented programming. In terms of languages, although not the only, the most commonly used in the different subjects is Python; if you don't know, it would be important that prior to the completion of the master's degree, basic knowledge about this language was acquired.
        • Knowledge in mathematics and statistics. In principle, the minimum level required would be the equivalent of those acquired in the first course of any degree in engineering.
        • For the data science part you'll need basic knowledge about machine learning techniques (for example, sorters induction: decision trees, etc.), as well as about experimental methodology for learning and data mining. A good reference to acquiring this knowledge is: Max Bramer, Principles of Data Mining, Springer. If you are a student of any of the three universities you can access the edition of 2016 of the book at the following URL:; it is also accessible from the library of any of the three. As necessary basic parts we advise reading the following chapters: 1-9, 12 and 14-15. If you don't have access to the book, the title of those chapters can help you search for information online.
        • To finish, Keep in mind that, given the contents addressed, We will use English literature and audiovisual material.

      In this Master we have only prepared a zero course for the UNIX Shell. For the rest, it's easy to find basic tutorials on the internet. If you need help about this, you can contact the Master's Coordinator.

    3. Technical Requirements

      In the Interuniversity Master's Degree in Business Intelligence and Big Data in Safe Environments the learning process is 100% Online, namely, you won't have to scroll to perform/deliver tasks. On our virtual campus you will have all the resources and you will carry out all the activities (including evaluation tests). To access the virtual campus you don't need advanced computer skills, you only have to operate your own desktop or mobile device with an updated Internet browser (we recommend always using Mozilla Firefox or Google Chrome).

      As the evaluation is continuous, you will be connected with the teachers and with the rest of the colleagues through the different communication tools; that's why you need a broadband Internet connection.

      Even if you don't have to scroll for testing, you should keep in mind that, in some subjects, tutoring or some evaluation test are conducted via videoconference, quoting you at a specific date and time. For this reason you need to have a webcam, headphones and microphone. For everything to work perfectly you must have a Microsoft Operating System (Windows 7 or later) or Mac (OS X 10.8 or later).

      During the course of the tests, the teacher will be able to activate the tools he deems appropriate to ensure the authorship of the tests and prevent fraud in them (anti-plagiarism software, facial recognition systems, etc.).

      At the time of your registration, the university where I've decided to do your tuition (well be the University of Burgos, Leon or Valladolid) provides you with an email account. It's very important that you check it often since all the notifications of the subjects will reach you in that mailbox.

      If you have any questions about the technical requirements for online titles use this form (

    In the FAQ tab ("FAQ") you can find more information about frequent doubts.

    Plan of studies

    The contents of the master's degree is organized in 5 materials, with 18 compulsory subjects:

    1. Computing for Big Data technologies.12Infrastructure for Big Data31
    Programming models for Big Data31
    Big Data architectures31
    Scalable storage31
    2. Science of data / Data Science9Scalable machine learning techniques32
    Learning about data flows32
    Knowledge Discovery / Unsupervised learning32
    3. Business intelligence / Business Intelligence15Financial concepts and tools of management in the company31
    Processing of data for business intelligence / Business Intelligence31
    Data visualization31
    I applied business/Business Intelligence32
    Applied business/Business Intelligence II33
    4. Data security and cybersecurity15Emerging trends in data security31
    Law on data security31
    Computer forensics and security audit31
    Foundations of cybersecurity32
    Emerging trends in cybersecurity32
    5. Master's Thesis9Master's Thesis92

    The Organization in matters presented in the table responds to the approach of the master: large amounts of heterogeneous information management (Big Data), with a double specialization: the use of that information for the analysis of the situation and support in decision-making of the enterprise and the safe management of such information (theme emerging at present).

    The first two courses focus on Big Data, more specifically, in its two fundamental problems:

    • Scalable data storage: matter 1 "Information technologies for Big Data". It includes everything related to the storage and access to large volumes of data, that, also, they can be heterogeneous, It is one of the additional features of Big Data.
    • Scalable data processing: matter 2 "Science of data/Data Science". As for the storage, the application of analytical techniques in large volumes of data, they have to rely on technologies appropriate to the way of storing, the type and the volume of data that is being treated.

    The study of each of the fields of specialization of the master within the Big Data is included in the materials 3 and 4, respectively:

    • Data analysis applied to the business world: matter 3 "Intelligence of business/Business Intelligence". One of the application fields most important from a practical point of view of the Big Data is related to the business world. This subject deals with everything related to this perspective. Includes a subject (Financial concepts and tools of management in the company) that will help you better understand the world of business and data handling; focused, above all, students of eminently technological profiles.
    • Secure data processing and management: matter 4 "Data security and cybersecurity". Important topic in any problem dealing with data. The distributed and heterogeneous nature of the information with which we are dealing, does that security in this field has its own characteristics, making this issue one of the emerging problems in the Big Data.

    Finally, There is the realization of a practical application of everything I learned in the described materials work, the Master's Thesis. The nature of this part makes that a matter be devoted to this work. As far as possible aim is to make this work within a company or research group, namely, linked to real problems.

    Course organization

    The course is organized in semesters, so, as a general rule, the basic subjects have been located in the semester 1, leaving for the second which need skills from other (located in the semester 1) or more specialized content.

    Within each semester it has been sought, as far as possible, have the minimum of subjects in parallel to balance the school load, minimizing overlap. The subjects have been sequenced taking into account the dependence on content.

    The subject Master's Thesis, TFM, is an exceptional case, dependent on the rest of subjects. For this reason, the semester 2 divides, about, in two parts according to the ratio of subjects (21 credits) and the TFM (9 credits). The first will teach the subjects corresponding to the semester, dedicating the last part to the realization of the TFM and its defence

    The distribution of subjects during the course is done as shown in the following figure (with the same background color is shown subjects that belong to the same subject):

    Educational Guides

    Course 2018-2019

    * Click on each subject to see your teacher guide

    Semester 1
    Infrastructure for Big Data1. Computing for Big Data technologies3Weeks
    1 to 5
    Programming models for Big Data1. Computing for Big Data technologies3Weeks
    5 to 9
    Big Data architectures1. Computing for Big Data technologies3Weeks
    9 to 13
    Scalable storage1. Computing for Big Data technologies3Weeks
    13 to 17
    Financial concepts and tools of management in the company3. Business intelligence / Business Intelligence3Weeks
    1 to 9
    Processing of data for business intelligence / Business Intelligence3. Business intelligence / Business Intelligence3Weeks
    9 to 17
    Data visualization3. Business intelligence / Business Intelligence3Weeks
    1 to 9
    Emerging trends in data security4. Data security and cybersecurity3Weeks
    1 to 15
    Law on data security4. Data security and cybersecurity3Weeks
    1 to 15
    Computer forensics and security audit4. Data security and cybersecurity3Weeks
    1 to 15
    Semester 2
    Scalable machine learning techniques2. Science of data / Data Science3Weeks
    1 to 7
    Learning about data flows2. Science of data / Data Science3Weeks
    6 to 12
    Knowledge Discovery / Unsupervised learning2. Science of data / Data Science3Weeks
    1 to 7
    Business/Business Intelligence applied I intelligence3. Business intelligence / Business Intelligence3Weeks
    1 to 12
    Business/Business Intelligence applied II intelligence3. Business intelligence / Business Intelligence3Weeks
    1 to 12
    Foundations of cybersecurity4. Data security and cybersecurity3Weeks
    1 to 12
    Emerging trends in cybersecurity4. Data security and cybersecurity3Weeks
    1 to 12
    Master's Thesis5. Master's Thesis9Weeks
    13 to 17


    General comments:

    • Each semester is divided into two parts, a part where subjects are taught (including TFM) and which includes the evaluation for the ordinary call for them and the final part, No teaching, reserved for the extraordinary call.
    • Holidays and vacation days are governed, en general, by the school calendar Spanish.

    Calendar 2023-2024

    Calendar 2022-2023

    Calendar 2021-2022

    Calendar 2020-2021

    Calendar 2019-2020

    Calendar 2018-2019

    Competencies – Learning results

    General competences
    CG1Acquisition of theoretical competences and practices for the analysis and design of business solutions in Big Data (storage and processing of large volumes of heterogeneous information).
    CG2Ability to plan and construct systems that allow secure data management.
    NG3Ability to design and implement systems able to extract practical knowledge of large volumes of data applied to the business world (Business/Business Intelligence Intelligence)
    Following the general approach that the leap between what has been learned and the requirements of the world of work is the smallest, the former General competences are specified in the following skills, divided by topics or major thematic blocks.
    Skills of computer technologies for Big Data:
    CBD1Ability to design and implement systems of knowledge in large distributed database discovery.
    NBD2Ability to analyze, design and build or configure scalable storage and scalable processing systems.
    Powers of science of data/Data Science
    CDS1Ability to apply, validate and evaluate methods of science of data/Data Science and Artificial Intelligence on sets and massive and complex data streams.
    CDS2Ability to lead projects for knowledge extraction based on efficient methods of data analysis.
    CDS3Capacity for analysis, exploration and synthesis of complex sets of unstructured data and design solutions that allow you to extract the same relevant and valuable information to support decision making.
    Powers of intelligence of business/Business Intelligence
    CBI1Acquisition of theoretical competences and practices on financial basics and company management, in four aspects: customers-marketing, staff, production and innovation.
    CBI2Ability to apply Business Intelligence in project development<strong></strong>optimization of the management of the company s (customers-marketing, staff, production and innovation), and the improvement of decision-making
    CBI3Ability to design and create visualizations based on information extracted from massive and complex data.
    CBI4Ability to analyze, design and implementation of applications that provide visualization of continuous mode on changing data streams.
    CBI5Ability to design, parameterize and build complex systems on specific tools business intelligence.
    CBI6Acquisition of theoretical competences and practices about the ETL process (extract, transform and load) on the data of the company, for the design and implementation of systems analysis and extraction of information in order to optimize the management and improve decision-making processes.
    Powers of safety in Big Data and cyber security
    CSD1Ability to use basic concepts of cybersecurity in projects of Big Data.
    CSD2Capacity for the implementation of systems security and meet audit and forensic analysis techniques, in the context of computer security and cybersecurity.
    CSD3Acquisition of theoretical competences and practices on management of the security of information systems.
    CSD4Ability to access, analyze and apply the information generated in security incident response centres, as well as its principles of operation and regulations.
    CSD5Ability to design and implement solutions regarding the aspects relating to security and privacy issues in Big Data environments.
    CSD6Know and apply the latest trends and emerging technologies in the field of security with applications to Big Data.

    Access and admission

    General criteria

    On the basis of the Royal Decree 1393/2007 of 29 October, to access official Master teaching it will be necessary to be in possession of a university degree.

    Access to the master will be governed by the rules of the UBU, the ULeon and grape for titles with seat and will be compliant with the General selection criteria the University. Add to these rules and general criteria specific selection requirements, Here you are, in the case that the number of pre-registered exceeds the annual offer of squares

    Specific criteria

    Form concrete, establishes the following specific access to the present Master profiles:

    A.. Suitable areas: Graduates in the field of technology, mainly with computer science degrees, but also other qualifications such as telecommunications, Industrial or electronic. Graduates in the field of science with competencies in math and computer science as physics, Statistics or math.

    B. Related areas: Graduates in architecture, Economy, Trade, Marketing, Business Administration, and other similar. In this case, they must have work experience demonstrated in the field of computer science (software development, systems management, project management, etc.) that trained them for a correct use of the master.

    Graduates (or equivalent degree) in A profile, you will have direct access. For graduates in the profile B raised the following specific access requirements:

    • Have general experience in the field of computer science.
    • Knowledge of computer science in software development, systems management, project management, etc..
    • Mathematical knowledge (algebra and calculus) and statistics (probability and inference) at the level of first degree course.

    Criteria for admission

    Where the number of pre-registered students exceed the places, the order of admission will decide the General Coordinator of Master Committee, to be assessed for admission, on a preferential basis, profile of candidates, According to his training to assimilate and take advantage of the knowledge of the master. Specifically, They shall be taken into account as criteria for admission: to access A profile University degree, scoring in the academic record of the degree, along with the curriculum vitae; also an advantage being in possession of a diploma of master in issues related to these studies.

    If there are free places, applicants with degrees in other areas (B access profile) they may be considered, but they must prove insufficient in the specific access requirements raised levels of knowledge. In order to decide about the level of knowledge of the candidates, the Commission will investigate the CV of applicants and can, If thus considered it, conduct a personal interview with each of them.

    However, Depending on each specific case, Coordinator of the Master General Committee may recommend to admitted students, prior to the start of classes, complementary training activities, for example, online courses, or other.

    Once admitted

    Once selected, admitted students to the study of the master, they will be called on the immediate dates prior to the start of the registration period, at a briefing where you instruct them the structure and development of the studies, materials and subjects that comprise it and teachers who give them.

    After the registration, assign each student a teacher among those who make up the teaching staff of the Master, taking into account, among other data, and to the extent possible, interests and the specific skills of the student.

    Official memory

    Outputs professionals

    The labour market related to the so-called "data economy" [1] is a booming market: According to the statistics compiled in the European Union, in 2016 There were a few 350.000 data in Spain and lathe-related jobs to 6 million throughout the European Union. Even with these figures, the demand for this type of professionals in the European Union currently slashing half a million jobs, with forecasts for a shortage of 800.000 posts in 2020. [1]

    Given the breadth of issues professional outputs for which enables the present master are very different. Between them they can be indicated:

    • Director of data (Chief data officer) within the company. The graduate will be trained to perform tasks of consultant, Analyst and implantation of policies of Government in terms of storage, management, use and safe access of the data within the different departments of the company.
    • Data engineer (big data engineer). The graduate will be trained to perform tasks of consultant, Analyst release & deployment architectures for Big Data Systems, in a secure environment, both enterprise and research groups.
    • Data scientist (data scientists). The graduate will be trained to perform Manager tasks, Head of project or analyst within the Department of enterprise business intelligence. You will be able to both address how to participate in the creation of systems or departments of analysis and recommendation. The same, You may exercise researcher / Coordinator of research projects on treatment and extraction of knowledge in large volumes of data.
    • Director of information security (chief information security officer). The graduate can perform consultant, Analyst and implantation of policies and management systems, both computer and legal, data.
    • Creation of a business to provide solutions to any level with Big Data, the science of data (data science) and business intelligence, in an environment that ensures the security and protection of data.
    [1] Emilio Ontiveros (dir.) and Verónica López Sabater (Coord.), "Data economy. Wealth 4.0 ", Editorial Ariel and Fundación Telefónica, 2017. Available in: (last access 18-05-2018)

    Team teaching

    The teaching staff is composed of university professors and experts from the business world.

    Each university teachers who will teach the course are:

    • University of Burgos: Dr. Mr. Juan José Rodríguez Díez, Dr. Mr. Cesar Ignacio García Osorio, Dr. Mr. Bruno Baruque Zanon, Dr. Mr. José Francisco Díez Pastor and Dr. Mr. Alvar Arnaiz Gonzalez
    • University of León: DRA. DNA. Henar Alvarez slope, DRA. DNA. Noemi de Castro Garcia, DRA. DNA. Adriana Suarez Crown, Dr. Mr. Miguel Carriegos Vieira, DRA. DNA. Lidia Sanchez Gonzalez, Dr. Mr. Miguel Angel Conde Gonzalez, DRA. DNA. Maria Teresa Trobajo de las Matas.
    • University of Valladolid: Dr. Mr. Belarmino Pulido Junquera, Dr. Mr. Carlos Alonso González, Dr. Mr. Carlos E. Lively Pascual, Dr. Mr. Quiliano Isaac Moro Sancho, Dr. Mr. Benjamin Sahelices Fernández, Dr. Mr. Arturo González Escribano, Dr. Mr. Fernando Díaz Gómez, Dr. Mr. Aníbal Bregón Bregón, Dr. Mr. Miguel Angel Martínez Prieto, Dr. Mr. Fernando Adolfo Tejerina Gaite, Dr. Mr. Javier Pajares Gutierrez and Dr. Mr. José Antonio Salvador Insua.

    University teaching and research staff of template is periodically subjected to an assessment of its work. Every five years is evaluated his teaching activity, granting a section teaching if this assessment is positive. The research activity is evaluated every six years; the evaluated merits are articles in journals of first international order, papers in conferences of high prestige and patent exploitation. Each positive assessment is a research section. The following table shows a summary of the qualifications of university teachers participating in the master:

    CategoryNumber of teachers
    Reaches teachersResearch sections
    Holders of University136129
    Hired Doctor484

    The following external professors will be teaching:

    • Mr. Alvaro Aparicio Lazarus. Senior IT Business Analyst – Computer Engineering – MBA – Executive Program in Big Data and Business Analytics. He has worked in companies like Indra, Philips and Everis. Is currently the Responsible for development and management of analytical systems in global Exchange, where performs functions of: development of new models of Business Analytics based on Big Data environments, new project management, development of applications for business process Analytics, definition of technical system architecture, development of management dashboards.
    • Mr. José Carlos Belloso Castle. Software developer and engineer of technical maintenance worldwide (Global Technical Support Engineer and Software Developer) of Varian Medical Systems. With experience, within the same company, as a developer of PSE (Process System Engineering) & Big Data, working with architecture and analysis of data based on the SPLUNK platform.
    • Dr. Mr. Juan Manuel Pascual Gaspar. Responsible of the master patient index (EMPI) of technical (Health of Castilla y León). PhD in computer science from the University of Valladolid and has a degree in physics and electronic engineering from the University of Granada. Professional experience in the development of information systems and telecommunications of long scale in international companies such as Telefonica and Accenture, He has taught, also, at the Miguel de Cervantes European University.
    • Dr. Mr. Jesus F. Rodriguez-Aragon. Software engineer and a PhD from the University of Salamanca, University of which he is an Associate Professor. He has worked for IBM, as researcher in the Group of Robotics and society at the University of Salamanca, founder and CEO of Techtrid, consiltoria technology company and has been director of MEGA-Spain, a subsidiary of Actually, is co-founder and CEO of IBerBox, a cloud for professionals and SMEs. Best computer engineer of the year award 2018, awarded by the Professional Association of engineers in computer science in Castilla y León
    • DNA. Isabel Fernández Isasi. Responsible for the area of Data Science of Madison MK, combining the management of equipment with the work of Data Scientist. Works in the development of predictive models solving business problems. A graduate in mathematics and Master Big Data and Business Analytics, He has participated in initiatives related to research as the summer residences of the scientist at the University of Valladolid Park program, including the second prize by the residence "Modeling of reactive consumption habits" in video games.
    • Mr. Jose Luis Marin of the Church. Head of the technological strategy of Madison MK and Director of the company Gateway S.R.L.. (owner of EUROALERT.NET). Telecommunication engineer graduate in business management and administration. He has directed more than 10 r & d projects in the area of technologies associated with Cloud Computing, Big Data and data science, performing, also, tasks for evaluation of projects of research and innovation for the European Commission. Author of various publications, It regularly participates in initiatives and events related to the momentum of the "open source" software, innovation and free and open knowledge and Open Data.
    • Mr. Julian Gomez square. Computer engineer and Master in Big Data and Business Analytics. It has a long history in the world of TI, new technologies and data analytics. He has worked in consulting firms and provided professional services for several companies in the field of design and product development, IT project management, definition and monitoring of strategic plans of architecture and systems. She has done projects of innovation in technologies applied in the business environment (Repsol, Endesa, Mains, Gamesa, Acciona, Globalia …), as well as coordinating technical teams in r & d projects. He is partner and co-founder of Analyticae, where she leads the area of architectures Big Data & Business Analytics.
    • Mr. Cristobal Rodriguez Fraile. Degree in political sciences and sociology, It is Big Data and Business Analytics Master and Master in human resources management. Consultant certificate in SAP Human Capital Management. Since in 1995 began her professional career, It has carried out its activity mainly in the area of human resources. He is partner and co-founder of Analyticae, where she leads the area of People Analytics. He has worked in all types of clients doing project management processes in all areas of human resources including dashboards and BI systems in clients like Banco Santander, Electrical network of Spain, Cosentino group, CEGASA, SAICA, HOLCIM, FINSA, ACCIONA or REPSOL among others.
    • DRA. DNA. Rocio Gonzalez Martinez. Senior consultant. A degree in mathematical sciences specialty statistics. PhD in Data Analysis. Has more of 20 years of experience in the area of data analysis and data mining. Responsible for the launch of IKEA in Portugal: launch of brand and opening of stores from the post of head of external communications of the country. Pioneer in the construction of predictive models, scoring of customers, Clustering, RFM models, analysis of the shopping cart, application of Big Data to the world of human resources, analysis of the customer lifecycle, testing of campaigns, etc., leading this area in Analyticae company of which he is a founding partner. He has worked for clients like IKEA, Makro, El Corte Inglés, Barclays, Fujistu, Self Trade Bank or IBM

    Associated companies

    master_empresas_aeiseguridadmaster_empresas_anfixmaster_empresas_beonpricemaster_empresas_cognizantcoritelmaster_empresas_cpiicylDatasalteuroalertEVERISLightIndra minsaitmleannmaster_empresas_plasticscmRoamsSILVERSTORMmaster_empresas_tecsidelmaster_empresas_telefonica_i + dvoxel3dmaster_empresas_xeridia


    • Coordinator General of the Master:
      • Carlos Enrique Vivaracho Pascual
        Associate Professor
        Department. Computing, University of Valladolid
    • Coordinator University of Burgos:
      • Bruno Baruque Zanon
        Assistant Professor Doctor
        Department. Languages and computer systems, University of Burgos
    • Coordinator University of Leon:
      • Henar Alvarez slope
        University Professor
        Department. Labour Law and Social Security
    • Coordinator School of Engineering Computing of Segovia:
      • Miguel Ángel Prieto Martínez
        Assistant Professor
        Department. Languages and computer systems, University of Valladolid

    Technical resources

    To be able to follow the course only requires a PC with connection to Internet, and two applications that come in the standard installation of any operating system: a browser to enter the virtual platform and a Remote Desktop client.

    For video conferencing (tutorials, classes online, submission of papers, etc.) you will need to have a webcam and a microphone. We will use Skype and Lifesize. In both cases the customer is free and very simple installation.

    Other tools and software you need will be provided in the virtual machines that will be assigned to each student or will be accessible via web (browser). For the Exchange and sharing of files, If necessary, Access will be provided for free to shared storage spaces.

    The virtual platform that we use is based on Moodle and the URL is: You can access it from any electronic device connected to the internet. Can also be accessed from the application Moodle Mobile (available in Google Market and Apple Store) that can be installed in Tablet or Smartphone.


    Previous Knowledge

    For the correct use of studies, the minimum prior knowledge that the student must have is:

    • General experience in the field of computing. You must have knowledge of managing a computer at both the user level and basic computer management. Data sets will be accessed and managed, therefore, student must possess basic knowledge in the field of databases.
    • Knowledge in software development. No big software projects are going to be done, but you do need to know how to program. You need to know object-oriented programming. In terms of languages, although not the only, the most commonly used in different subjects is Python; if you don't know, it would be important that prior to the completion of the master's degree, basic knowledge about this language was acquired.
    • Knowledge in mathematics and statistics. In principle, the minimum level required would be the equivalent of those acquired in the first year of any engineering degree.


    Is it necessary to reside in Spain to study the Master?

    Not, You can register and access it from anywhere in the world provided that you meet the requirements of access and admission.

    How much is the Master?

    The cost of the ECTS credit is the same that has any non-professional face-to-face master (Master's degrees that enable the exercise of professional activities regulated in Spain) in any of the public universities of Castilla y León. The Junta de Castilla y Leon is responsible for setting those public prices each course. Prices are updated and available on the website of any of the participating universities in the title.

    I have to enroll in the? 60 credits?

    It is the ideal, but it is not obligatory. All universities involved in the master's degree have the option to make partial tuition for business reasons. Concrete information is available on the website of each University.

    What University I matriculate?

    You can enroll in any of the three universities involved in the Master. The limitation of vacancies of the master extends to each University and Centre. Each University is limited to access from 9 students, distributed, of Valladolid, 6 School of computer engineering in Valladolid and 3 for the Segovia. If you exceed the limit in one of them, It informed you of the free places that will remain in the rest.

    You have any implications to enroll in one or another University??

    No. Regardless of where you matricules, you will have the same rights and availability of resources. The final title is also the same.

    Do they have the same title online to the classroom?

    Yup. A master is verified by the National Agency for quality assessment and accreditation (ANECA). This means that they have the same validity as any person evidence offered by any University.

    Have the same level of quality as the face-to-face studies online?

    Yup. The quality of studies depends on much of the quality of teachers that are available. The teachers who will be teaching have a wide teaching experience, both face-to-face qualifications as virtual, to provide you the skills that employers are looking for in the real world. In this way, We ensure that you will receive the same high quality training academic qualifications face-to-face students receiving.

    At how many calls can I submit with each registration?

    You have the right to introduce you to two calls in each of the subjects that you matricules: a regular call to the end of the first semester classes and an extraordinary announcement in which you could recover the subjects not overcome in the ordinary.

    What services I get?

    As a university student you have the same rights and access to the same services as any other student of the face-to-face courses, in any of the universities.

    How can I access to the virtual classroom (UBUVirtual)?

    To access the virtual classroom of any subject must be enrolled in the same. To access only you need a browser with Internet connection and sign in via a username and password which you will provide to the register. Within the virtual classroom, You can access all materials and activities, as well as participate in the discussion forums, in the virtual tutorials, etc..

    How studied is in the online platform?

    You must keep in mind that in the educational model in the master, the student is the protagonist of the learning, so you will have an active role within this process. Studying online does not mean you study alone, Since through virtual platform you will be in touch with your classmates and teachers. Within the virtual classroom, you will have access to all available resources within each subject organized by topics. In each subject, the teachers of the subject will propose you a series of activities that are part of the continuous evaluation of the subject. So you can better plan your, There will be a calendar with the dates of delivery of all activities.

    Some of the activities that you perform will be individual, but others will be carried out collaboratively together with your fellow students within virtual environments. All these activities will be delivered through Virtual Classroom, so the Professor can make appropriate corrections and alert you when publish ratings.

    What is the role of the tutor?

    Will assign each student a tutor. This assumes a role of reference and guidance throughout the course. Its aim is to assist and guide students in their learning process through a comprehensive and personalized monitoring of student. Also, It will guide you in your transition to the world of work and career development. It will also be the reference for any problem that might arise, making contact between the student and the General Coordinating Commission of the master.

    What teaching methodologies are followed in online delivery?

    The teaching method of teaching is based on a Moodle-based virtual teaching platform that helps and makes it more dynamic and interactive with students. Offering the possibility of access to class material, lectures and other exhibition techniques, with autonomous activities (directed works and readings), problem-based learning and/or projects, along with follow-up tests through tests and online tasks.

    Who else accompanies me on this online journey?

    During the conduct of the studies, coordinators and teachers guide your learning, but your teammates also play an important role. The virtual platform promotes collaborative learning, active participation and great importance is given to group learning with participation in forums and other alternative collaborative means such as online tutoring, workshops, etc..

    Updated 23 in October of 2023: Updated regulations for the election of delegates