Degree in Data Science

(CG05) Analysis and synthesis capability in the preparation of reports and in the defence of ideas.
(CG06) Ability to access and manage information in different formats for subsequent analysis in order to obtain knowledge from data.
(CG07) Ability to autonomously make decisions and to properly and originally elaborate reasoned arguments, in order to obtain reasonable and contrastable hypotheses.
(CT01) To be able to access (bibliographical) information tools and appropriately use them in the development of their daily tasks.
(CT02) To be able to complete technical, scientific, social and human training in general, and to organise self-learning with a high degree of autonomy.
(CT03) Ability to defend your own work with rigor and arguments and to expose it in an adequate and accurate way with the use of the necessary means.
(CT04) To be responsible for ones own professional development and specialisation, applying the acquired knowledge in the identification of career opportunities and sources of employment.
(CT05) Ability to evaluate the advantages and disadvantages of different methodological and / or technological alternatives in different fields of application.
(CE01) Ability to solve the mathematical problems that can be posed in data science and be able to apply knowledge on: linear algebra, differential and integral calculus and numerical methods and optimisation.
(CE02) To methodologically know and apply the programming techniques and the algorithms necessary for the efficient processing of information and the computer resolution of problems that use large volumes of data.
(CE03) Ability to solve classification, modelling, segmentation and prediction problems from a set of data.
(CE04) To know and use the different models of data storage and database management systems using programming languages for the definition, query and handling of data.
(CE05) To understand the most relevant fields of application of data science and understand how data science is used to base and perform decision-making based on data
(CE06) Ability to represent and visualise data sets for the extraction of knowledge.
(CE09) To methodologically know and apply the concepts and techniques of probability and statistics necessary for the extraction of useful knowledge from data analysis.
(CE10) Ability to digitally process signals and extract information from them.
(CE11) Ability to design and implement data acquisition, its integration, transformation, selection, verification of its quality and veracity from different sources, taking into account its character, heterogeneity and variability.
(CE12) Ability to design and start solutions based on data analysis in the field of medicine and business, taking into account the specific requirements of this type of use cases.
(CE13) To know how to design, apply and evaluate data science algorithms for the resolution of complex problems.
(CE14) To understand and apply the ethical, legal and normative aspects related to data treatment and the application of the obtained knowledge.
(CE15) Ability to model and analyse the uncertainty in data-based studies, as well as to know how to interpret and contextualise the results obtained.
(CE16) Ability to develop an original exercise, to do it individually, as well as to present it and defend it before a university board, on the field of data science, in which the acquired competences are synthesised and integrated in the lessons.
(CG01) Knowledge of basic subjects and technologies that enable students to learn new methods and technologies, and to provide them with versatility to adapt to new situations.
(CG02) Ability to solve problems with initiative and creativity and to communicate and transmit knowledge, abilities and skills, which should include the ethical and professional responsibility of the activity of a data scientist.
(CG03) Capability to elaborate models, calculations, reports, to plan tasks and other works analogous to the specific field of data science.
(CG04) Ability to work in a multidisciplinary group in a multilingual environment and to communicate, orally and in writing, knowledge, procedures, results and ideas related to data science.
(CE07) Ability to model dependency between a response variable and several explanatory variables, in complex data sets, using machine learning techniques, interpreting the results obtained.
(CE08) Ability to understand, select and use the infrastructure and the techniques used to handle mass data, according to criteria of efficiency, scalability, security, error tolerance and adaptation to the production environment.
(CB5) Students must have developed the learning skills needed to undertake further study with a high degree of autonomy.
(CB4) Students must be able to communicate information, ideas, problems and solutions to both expert and lay audiences.
(CB3) Students must have the ability to gather and interpret relevant data (usually in their field of study) to make judgements that take relevant social, scientific or ethical issues into consideration.
(CB2) Students must be able to apply their knowledge to their work or vocation in a professional manner and have acquired the competences required for the preparation and defence of arguments and for problem solving in their field of study.
(CB1) Students must have acquired knowledge and understanding in a specific field of study, on the basis of general secondary education and at a level that includes mainly knowledge drawn from advanced textbooks, but also some cutting-edge knowledge in their field of study.
TI6 - Ability to design systems, applications and services based on network technologies, including the Internet, the web, e-commerce, multimedia, interactive services and mobile computing.
SI1 - Ability to integrate ICT solutions into business processes in order to meet the information needs of organisations, thus enabling them to achieve their goals effectively and efficiently and providing them with competitive advantage.
SI2 - Ability to determine the requirements of an organisations information and communication systems, considering safety aspects and compliance with regulations and legislation.
SI3 - Ability to actively participate in the specification, design, implementation and maintenance of information and communication systems.
SI4 - Ability to understand and apply the principles and practices of organisations, so that they can liaise between the technical and administrative staff of an organisation, and can actively participate in the training of users.
SI5 - Ability to understand and apply the principles of risk assessment and apply them correctly in the development and implementation of action plans.
SI6 - Ability to understand and apply the principles and techniques of quality management and technological innovation in organisations.
IC2 - Ability to analyse, evaluate and select the most appropriate hardware and software platforms to support embedded and real-time applications.
IC1 - Ability to develop specific processors and embedded systems, and to develop and optimise software for such systems.
IC3 - Ability to analyse, evaluate, select and configure hardware platforms for the development and implementation of computer applications and services.
C1 - Ability to know the fundamentals, paradigms and techniques in the field of intelligent systems, and to analyse, design and build computer systems, services and applications that use these techniques in any field of application.
C2 - Ability to acquire, obtain, formalise and represent human knowledge in a computable form for solving problems through a computer system in any field, particularly in those related to aspects of computing, perception and action in intelligent environments.
C3 - Ability to recognise and develop computational learning techniques and to design and implement applications and systems that use them, including those for the automatic retrieval of information and knowledge from large volumes of data.
Capacidad para participar activamente en la especificación, diseño, implementación y mantenimiento de los sistemas de información y comunicación.
G1 - Be able to relate and structure information from different sources and to integrate ideas and knowledge. (RD1393/2007)
G2 - Have the learning skills needed to undertake further studies or to gain further training with a certain degree of autonomy. (RD1393/2007)
G3 - Take into account the economic and social context in engineering solutions, be aware of diversity and multiculturalism and ensure sustainability and respect for human rights and equality between men and women.
G4 - Be able to integrate into working groups and collaborate in multidisciplinary environments and be able to communicate properly with professionals from all fields.
I10 - e able to design and evaluate human-computer interfaces that ensure accessibility and usability of computer systems, services and applications.
MM1 - Have knowledge and ability to understand essential facts, concepts, principles and theories related to multimedia systems including all the disciplines covered by these systems.
MM2 - Be able to understand and manage the different technologies involved in multimedia systems, both from the point of view of hardware and electronics and of software.
MM3 - Be able to implement methodologies, technologies, processes and tools for the professional development of multimedia products in a real context of use by applying the appropriate solutions for each environment.
MM6 - Conceive, design, and implement projects related to multimedia products by using engineering methodologies, applying the principles of human resources management and applying economic principles.
MM7 - Be able to apply the principles of audiovisual graphic design and communication to multimedia products.
MM9 - Program correctly in the different specific languages of multimedia systems taking into account time and cost restrictions.
MM10 - Be able to analyse and integrate software components to develop multimedia applications.
MM11 - Have knowledge and ability to apply the different mechanisms and elements to create both linear and non-linear audiovisual stories according to different production formats, technologies and media.
MM21 - Communicate effectively, both in writing and verbally, knowledge, procedures, results and ideas related to ICT and specifically to multimedia, and know their socioeconomic impact.
MM24 - Be able to design, develop, evaluate and ensure the accessibility, ergonomics, usability and security of multimedia systems, services and applications and of the information that these manage.
MM28 - Be able to solve problems with initiative, decision-making and creativity and to communicate and transmit the knowledge, abilities and skills of a multimedia engineer.