Data Science and Engineering

Basic Information

What knowledge will I acquire with this Degree?

A graduate in data science and engineering will develop a multidisciplinary vision of engineering, capable of facing the challenges posed by an evolving technological environment and largely based on computer systems that generate, process and analyze massive amounts of data. Graduates will be able to help respond to the growing demand for decision-making based on large volumes of information, providing adequate data treatment and analysis.

Where will I be able to work when I graduate?

The job opportunities of the graduates, as well as the expectations of their future evolution, are extremely positive. Both nationally and internationally, the demand for professionals has not stopped increasing in recent years, currently standing at the top of the labor market. In Spain this demand grows approximately at a rate of 30% each year. The presence of data systems in practically all areas (financial, industrial, infrastructure, public services, health, transport, etc.) means that this demand continues to increase.

Is this Degree official according to the regulations required by the European Higher Education Area?

Yes (final verification report is attached), the implementation of the degree will be done progressively, starting the first year in the academic year 2022-23.

The final verification report turned out FAVORABLE

What subject areas will I address in this grade?

The Degree in Data Science and Engineering is divided into seven modules of knowledge, each of them being structured in different subjects, as reflected in the following table.

MODULE	ECTS CREDITS	CONTENTS
1. Common Core Knowledge Module	18	This module includes the subjects common to all the degrees that can be taken at the URJC.
2. Branch basics module	36	Here the basic training subjects for the degrees of the Engineering branch, in which this Degree is framed, are grouped.
3. Mandatory knowledge module	135	This module includes the subjects that make up the main body of the degree.
4. Optional knowledge module	9	Here are subjects that complement the student's training, allowing him to achieve a certain degree of specialization in the chosen subjects.
5. External internship module	15	The student will carry out internships in companies or institutions in which they will develop activities that will complement their training.
6. Academic credit recognition module	0	This module is passed through the participation of the student in sports university activities, student representation, solidarity and cooperation.
7. Final Degree Project Module	15	As the last subject, the student will carry out a Final Degree Project in which they will put into practice the skills acquired throughout the degree.

The subjects of modules 1, 2, 3 and 4 are included in the following subjects:

RAW MATERIAL	ECTS CREDITS (MANDATORY/OPTIONAL)
1.1. Humanities	6 / 0
1.2 Computing	6 / 0
1.3. Deontology	6 / 0
1.4. Language	6 / 0
2.1. Math	12 / 0
2.2. Physics	6 / 0
2.3. Statistics	12 / 0
2.4. Company	6 / 0
3.1. Computer Architecture	15 / 0
3.2. Math	9 / 0
3.3 Computing	30 / 0
3.4. signs	12 / 0
3.5. optimization	6 / 0
3.6. Data Science	39 / 0
3.7. Data Engineering	24 / 0
4.1. Integrated Projects	0 / 9
4.2. signs	0 / 4,5
4.1. Data Science	0 / 4,5

Recommended Income Profile

As an income profile, no restrictions other than those established by law (EVAU) are imposed. It is recommended that the student has training and a good predisposition for scientific-technical subjects such as mathematics and physics, as well as curiosity about the field of engineering and information technology, data, computing and communications. In general, people who have completed the Baccalaureate in the Science modality or, where appropriate, an equivalent modality of Baccalaureate or similar in terms of the subjects studied will have adequate training when the student comes from educational systems other than Spanish. .

For students from Vocational Training, access through Higher Level Training Cycles is recommended, where content belonging to the field of information technology and communications predominates.

Objectives

The fundamental objective of the Degree in Data Science and Engineering is to respond to the growing demand for specific training of professionals in a field that is leading to numerous economic and technological changes in the private and public sectors, both nationally and internationally. world level.

Competences

General Competences

Custom code	Description
CG01	Know basic subjects in the scientific field that provide students with a solid foundation for understanding and learning new models and tools, providing them with the ability to adapt to new knowledge throughout their academic and professional lives.
CG02	Understand and use subjects, models and tools in the field of data science and engineering that allow understanding the fundamental scientific-technical problems in this field, as well as evaluating the advantages and disadvantages of different methodological alternatives.
CG03	Conceive, develop and maintain computer systems, services and applications using engineering methods as an instrument for quality assurance.
CG04	Use and apply technological products and technology trends, associated with the field of data science and engineering.
CG05	Solve problems with initiative and creativity.
CG06	Be able to build models, perform calculations, write reports, plan tasks and other similar tasks in the specific field of data science and engineering, attending to the basic principles of analysis and synthesis capacity, expository clarity and scientific rigor.
CG07	Work in a multidisciplinary group and in a multilingual environment, interacting fluently with engineers and professionals from other disciplines, and communicating, both in writing and orally, knowledge, procedures, results and ideas related to data science and engineering.
CG08	Make decisions autonomously, preparing reasoned arguments in an appropriate and original way, thus being able to obtain reasonable and testable hypotheses and derive appropriate conclusions.
CG09	Access and manage information in different formats for later analysis in order to obtain knowledge from data
CG10	Communicate and transmit knowledge, abilities and skills, integrating social, environmental, economic and ethical aspects inherent to engineering, analyzing its impacts, and committing to the search for solutions to challenges of sustainable development.

Specific Competences

Custom code	Description
CE01	Skillfully use fundamental mathematical concepts and methods, applying knowledge of: linear algebra, differential and integral calculus, graphs, tensors, and numerical methods underlying data science and engineering problems
CE02	Analyze and model the uncertainty present in data-based studies, as well as knowing how to interpret and contextualize the results obtained.
CE03	Know and manage the concepts, models and tools related to mathematical optimization and, especially, to numerical optimization, as well as its direct application to problems related to data science and engineering.
CE04	Know and manage the concepts, models and tools related to the theory of information, signal and linear systems for use in the analysis and processing (deterministic and random) of information defined in regular domains, including sound, image, video and time series.
CE05	Understand and methodologically apply the programming techniques and algorithms necessary for the efficient processing of information and the resolution of problems through computerized means.
CE06	Know and use the different data storage models and database management systems using their definition, query and manipulation languages.
CE07	Design, apply and evaluate algorithms and data structures to solve complex problems with changing objectives.
CE08	Understand the fundamentals of data processing and exchange infrastructures: hardware, operating systems, architectures, and computer networks.
CE09	Model the dependency between a response variable and several explanatory variables, in complex data sets, using advanced statistical techniques (including regression methods, Bayesian inference, etc.) and machine learning methods, evaluating and interpreting the results obtained.
CE10	Use different data modeling, data analysis and machine learning techniques: choose and use appropriate techniques, evaluating the quality of the models, validating them, interpreting them and proposing improvements.
CE11	Design and implement data collection, its integration, transformation, selection, verification of its quality and veracity from different sources, taking into account its nature, heterogeneity and variability.
CE12	Effectively communicate the analysis process based on the data and knowledge of the problem and the interpretation of its results, selecting and using the most appropriate visualization techniques and tools.
CE13	Know the security requirements (with an emphasis on privacy) of massive data volumes, their associated protection measures at the technical, organizational and legal levels.
CE14	Understand, select and use the appropriate infrastructure and technology to design and implement processing flows of large volumes of data in "batch" or "streaming", taking into account criteria of efficiency, scalability, security, fault tolerance and adaptation to the production environment .
CE15	Use the necessary tools to access and store data and design data collection, integration, storage, processing and analysis systems in multidisciplinary applications.
CE16	Define, evaluate and select software and hardware for the development of systems in the field of cloud computing, understanding the peculiarities of the different platforms on which these systems must be executed.
CE17	Know the ethical, legal, regulatory and security aspects that apply in the protection, treatment and exploitation of data, as well as in the knowledge derived from them.
CE18	Know the applicability of data science and engineering in the current informative and technological ecosystem, as well as the fundamentals to articulate projects in this field.
CE19	Know part of the uses, methodologies and work tools in the professional field, related to the discipline of data science and engineering, adapting and applying a significant subset of the skills acquired in the Degree in Data Science and Engineering.
CE20	Perform individually and present and defend before a university court an original work, consisting of a project in the field of specific technologies of data science and engineering, of a professional nature, in which the skills acquired in the teachings are synthesized and integrated of the Degree in Data Science and Engineering.
CE21	Properly understand the concept of entrepreneurship and technology companies, as well as their legal framework, financing and business plans.

Transversal Competences

Custom code	Description
CT01	Communicate effectively in the foreign language of relevant professional and scientific use.
CT02	Develop appropriate extra-curricular skills for the comprehensive training of the graduate.

Minimum stay requirements

The permanence of the students in the Degree studies will be of a maximum of eight years for full-time students. Part-time students may request an extension of up to two more years from the Rector.
In Bachelor's degrees lasting more than 240 credits (4 years), the maximum of the previous section will be increased by one more year for every 60 ECTS credits that are added to the 240 ECTS.
Count as years of permanence those in which the student has formalized his registration and has not canceled it or his registration has been canceled due to non-payment.
Students must pass a minimum of two subjects in the first year. Students studying part-time must pass at least one subject in their first academic year.
Students who are studying any official Bachelor's degree at the Rey Juan Carlos University may make a maximum of four registrations to pass each of the subjects of the study plan, without counting previous cancellations of the same.

For more information see: Permanence regulations

Minimum number of ECTS credits by type of enrollment and course

Full-time students:

COURSE	MINIMUM	MAXIMUM
1º Course	48 ECTS	78 ECTS
Other courses	48 ECTS	78 ECTS

Part-time students:

COURSE	MINIMUM	MAXIMUM
1º Course	24 ECTS	47 ECTS
Other courses	24 ECTS	47 ECTS

Access and registration

Log in

Access to the official teachings of Degree will require to be in possession of the bachelor's degree or equivalent and the passing of the test referred to in article 42 of the Organic Law 6/2001, of Universities, modified by Law 4/2007, of April 12, without prejudice to the other access mechanisms provided for by current regulations.

The number of places offered for new admission are:

Fuenlabrada Campus:

40 places

Matriculation year

The enrollment process at the Rey Juan Carlos University is done through the Internet. You can carry out the procedures on the computers installed on campus or through any computer with network access. You can check the deadlines at registration , as well as the different requirements and necessary documents.

Validation with FP qualifications

PROFESSIONAL TRAINING DEGREES

HIGHER TECHNICIAN IN INTERNATIONAL TRADE (APPLICABLE FROM THE 2023-2024 COURSE)

HIGHER TECHNICIAN IN TRANSPORT AND LOGISTICS (APPLICABLE FROM THE 2023-2024 COURSE)

SENIOR TECHNICIAN IN NETWORK COMPUTER SYSTEMS ADMINISTRATION (ASIR) (APPLICABLE FROM THE 2023-2024 ACADEMIC YEAR)

SENIOR TECHNICIAN IN MULTIPLATFORM APPLICATION DEVELOPMENT (DAM) (APPLICABLE FROM THE 2023-2024 ACADEMIC YEAR)

SENIOR TECHNICIAN IN DEVELOPMENT OF WEB APPLICATIONS (DAW) (APPLICABLE FROM THE 2023-2024 ACADEMIC YEAR)

Training itinerary

ACCESS THE COURSE GUIDES OF THE DEGREE

FBC: Common Basic Training, they are validated with their counterparts of all grades
FBR: Basic Branch Training, they can be validated with their branch counterparts, taking into account the adequacy between the skills and knowledge acquired.
OB: Compulsory
OP: Optional

COURSE 1
Semester	Subject	Character	Credits
1	Linear algebra	FBR	6
1	Calculation	FBR	6
1	Fundamentals of Data Science and Engineering	FBC	6
1	Programming Fundamentals	FBC	6
1	Physical Foundations of Computers	FBR	6
2	Computer Structure	OB	3
2	Mathematical Tools for Data Science I	OB	3
2	Probability and Simulation	FBR	6
2	Entrepreneurship	FBR	6
2	Legal and Ethical Aspects	FBC	6
2	Mathematical Tools for Data Science II	OB	6
TOTAL COURSE: 60 ECTS

COURSE 2
Semester	Subject	Character	Credits
1	Statistical inference	FBR	6
1	Data Structures and Object Oriented Programming	OB	6
1	Signals and Systems	OB	6
1	Computer Architecture	OB	6
1	Optimization I	OB	3
2	Computer network	OB	6
2	Operating Systems and Virtualization	OB	6
2	Machine Learning I	OB	6
2	Regression Models	OB	6
2	Optimization II	OB	3
Annual	modern language	FBC	6
TOTAL COURSE: 60 ECTS

COURSE 3
Semester	Subject	Character	Credits
1	Mathematical Foundations of Information	OB	6
1	Distributed Data Processing Systems I	OB	6
1	Machine Learning II	OB	6
1	Design and Analysis of Algorithms	OB	6
1	Databases	OB	6
2	Data Security and Privacy	OB	6
2	Bayesian methods	OB	6
2	Time Series Analysis	OB	6
2	Distributed Data Processing Systems II	OB	6
2	High Performance Architectures and Cloud Computing	OB	6
TOTAL COURSE: 60 ECTS

COURSE 4
Semester	Subject	Character	Credits
1	Non-Relational Databases	OB	6
1	Information Display	OB	4,5
1	Data Processing in Irregular Domains	OB	4,5
2	Optional 1	OP	4,5
2	Optional 2	OP	4,5
1	Academic Recognition of Credits	OB	6
Annual	Final Degree Project	OB	15
Annual	External Internships	OB	15
TOTAL COURSE: 60 ECTS

ELECTIVES MODULE
Course	Semester	Subject	Subject	Credits
4	2	Data science	Natural Language Processing and Text Mining	4,5
4	2	Integrated Projects	Multidisciplinary Applications I	4,5
4	2	Signs	Multimedia Data Analysis	4,5
4	2	Integrated Projects	Multidisciplinary Applications II	4,5

Material resources

External Internships

The External Practices subject is a curricular subject whose main objective is to promote a comprehensive training of the student through the practical application of the knowledge acquired during the Degree, which facilitates direct contact with the professional activity and the opportunity to join the professional world with a minimum of experience. All practices are designed so that the students who participate in them acquire professional experience in real situations and conditions, applying the knowledge, skills and attitudes that are acquired in the training processes throughout the degree. The internships represent a decisive opportunity for the personal development and professional future of the students.

The internships are aerospace_vehicles_aerospace_engineering activities carried out by the student in companies, institutions and organizations; that is, in centers outside the university premises, which aim to enrich and complement your university education, while providing you with a deeper knowledge about the skills you will need once you have graduated.

The External Practices subject will consist of two phases:

Completion of the internship period that offers professional experience related to any of the graduate profiles that are expressed in the Verification Report of the degree.
Elaboration of the memory

Documentation:

Degree Training Project

For more information: External Internship Unit

Social Security contributions for interns starting January 1, 2024

Academic Recognition of Credits

Regulations for academic recognition of credits in undergraduate studies

Mobility programs

ERASMUS

The Erasmus program makes it easy for URJC students -both undergraduate and postgraduate- to study one or several semesters at one of the European universities with which the URJC has agreements.

These exchanges traditionally have an economic endowment thanks to the Erasmus Scholarships provided by the EU and the Spanish Ministry of Education.

ERASMUS (intranet)

WORLD

The Munde program manages mobility with universities from countries not included in the Erasmus Program.

The possibility of obtaining a scholarship or economic endowment and its amount depends, in each case, on the agreements with the universities, countries or entities that sign it.

WORLD (intranet)

For more information:

URJC Mobility

SICK

SICUE is a national mobility program for GRADOS university students that allows them to carry out part of their studies at another Spanish university with guarantees of academic recognition, use and adaptation to their curricular profile.

SICUE Mobility

Student support programs

Orientation to future students. The University offers various orientation programs for future students: we carry out visits to high schools and secondary schools, we organize guided visits to the Campuses, we are present in the Classroom and, at the beginning of each course, we carry out welcome days to guide students new students.

academic tutorials. Each teacher carries out, within their teaching planning, academic tutorials on their subject.

Coordinator of the degree. It works to promote coherence and balance between the subjects and the workloads of the students.

mentoring program. The URJC has this program, peer tutoring, in which the students of the last years act as mentors with the first year students.

Students with disabilities. The Support Office for Persons with Disabilities offers guidance and assistance to students with special needs.

Scholarships . The Rey Juan Carlos University manages the main scholarships and annual grants, both its own and from other official bodies: Ministries, Community of Madrid, International Organizations and other entities. It also publishes and disseminates those scholarships and grants of interest to its students and graduates. Throughout the course, students receive information about them through the different communication channels established.

Job placement program. The Rey Juan Carlos University, through the External Internship Unit and the Graduates Office, organizes conferences, workshops and various actions aimed at supporting and guiding students in their job search, to improve their employability and promote job placement . The University has a Job Exchange -a platform available to companies and graduates- where institutions can carry out their selection processes.

Regulation

ACADEMIC CALENDAR

Academic Calendar

REGISTRATION

*The rates corresponding to double degrees with different degrees of experimentality will be applied as established in the new Decree 43/2022, of June 29, of the Government Council, which establishes the public prices for university studies leading to official degrees and services of an academic nature in the public universities of the Community of Madrid*

TRAINING PROCESS

REVIEWS AND REVIEWS

Validation, adaptation of studies, recognition of credits and homologation of foreign qualifications

UNIVERSITY DEGREES

Extinction of university degrees

VISITING STUDENTS AND FUNCTIONAL DIVERSITY

COEXISTENCE REGIME

Coexistence Regulations of the Rey Juan Carlos University for the Development of Law 3/2022, of February 24, on University Coexistence, approved by Agreement of March 30, 2023, of the Governing Council of the University

SCHOOL INSURANCE

School insurance

ASSOCIATIONS

Regulation of student associations

Quality guarantee

RUCT link

BOCM Link

Internal quality assurance system

Manual of the Internal Quality Assurance System

Composition of the commission

Composition of the Commission

Results report

Once the follow-up has been carried out, the quantitative information on the results obtained in the follow-up of said Degree is shown, differentiated by academic year.

2022/2023

General information collection plan

Within the quality assurance system of the Rey Juan Carlos University, the following surveys are planned:

- New students

- Teacher evaluation

- Student satisfaction

- Satisfaction of the graduates

- Labor insertion

- Causes of abandonment

- Career path:

Second year after graduation
Third year after graduation
Fourth year after graduation

- Degree of satisfaction:

Faculty with the campus and university
Teacher with degree
of the evaluators
Incoming student mobility program
Outgoing Student Mobility Program
Administration and services staff with the university

- External internships:

Student satisfaction
External tutor satisfaction
Evaluator satisfaction

Survey results:

Indicators 2022/23

Improvement actions

The Quality Assurance System of the Rey Juan Carlos University establishes that the degree's Quality Assurance Commission will annually analyze the information derived from the degree's indicators and prepare a report that will include improvement plans if the results so indicate.

Improvement actions 2022/23

Renewal of accreditation

The renewal of the accreditation represents the culmination of the implementation process of the official Bachelor's and Master's degrees registered in the Register of Universities, Centers and Degrees (RUCT). The renewal of the accreditation of official bachelor's and master's degrees is organized in three phases: self-assessment report, external visit and final assessment.

In the first phase, the university describes and assesses the status of the degree with respect to the established criteria and guidelines. The result is the Self-Assessment Report (IA) that is presented. The second and third phases are carried out by a group of evaluators external to the evaluated title.”

Tracking

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