Master’s Degree in Data Science *
Take your career into the future and become an expert in one of the most in-demand professions
Data science is a discipline that has gained great relevance in the last decade due to the enormous amount of information that is produced and the value that it can bring to companies and organizations. The Master's Degree in Data Science that we offer is an excellent option for those who want to train in this area, and be at the forefront of creating data-based learning models, and of the analysis and visualization of information. This discipline needs qualified professionals and is currently one of the most demanded in the labor market.
Our master's degree is taught by a team of highly qualified professors, with experience in industry and academia, and who are committed to providing a quality education to our students. In addition, our hands-on approach sees students apply what they learn to real projects, allowing them to gain experience using cutting-edge tools and technologies in the field of artificial intelligence. This will allow them to be prepared to work in any environment, from startups to international companies, in a multitude of sectors: finance, health, electronic commerce, automotive and aeronautical industry, manufacturing and production, transportation, logistics, insurance, education, energy, environment, entertainment, construction, sports, advertising, marketing, cybersecurity, and scientific and academic research.
This exclusive program has a clear professional orientation, and is an ideal complement for professionals in the technology sector: university graduates in Mathematics, Physics and Engineering (informatics, industrial technologies, mechanics, automotive, telecommunications, industrial and automatic electronics, aerospace, industrial design and product development, bioinformatics, biotechnology, biomedical, software, computers, multimedia).
Nebrija University organized a TEDx event for the third consecutive year, which took place on March 24 at the Madrid-Princesa Campus, and was part of the year-long celebration of the 5th Centenary of Antonio de Nebrija. Under the title Alphas: the impregnable algorithm, TEDxUNebrija vindicated the validity of humanism in today's world and reflects on what is unique in the human being as a way of surviving the expansion of machines.
Student profile:
The admission profile for this Master's Degree in Data Science includes:
-Graduates in Engineering, particularly those with a Bachelor's Degree in Computer Engineering or equivalent degrees from the previous system (such as Technical Engineers in Management Computing, Technical Engineers in Systems Computing, and Computer Engineers). This also includes related degrees in the field of Computer Science, such as Bachelor's in Information Systems, Software Engineering, or Computer Engineering.
-Graduates in quantitative disciplines, such as Mathematics, Physics, and Statistics.
Official Degree:Master’s Degree in Data Science
Center responsible:Higher Polytechnic School
Openings available: 100 online
Total Crrdits 60 credits.
Minimum of 12 ECTS credits and maximum of 60 ECTS credits per enrollment and academic period.
Academic year in which it was implemented: 2023 - 2024
Duration: 1 year. From october to june
Type of Education: Online
Academic Regulations: General student’s regulations. Credit transfer and recognition. Regulation of student participation. Common procedures for carrying out the Final Research Project
University Services: [+info]
Internal Quality Assurance System System managers Incidents, Suggestions and Complaints Job placement report and assessment of training received
Get ready to lead digital innovation
Curriculum
The student must take 60 credits
First Semester 30 ECTS
- 3 ECTS | Mathematical Models for Machine Learning
- 6 ECTS | Programming Languages for Data Science
- 6 ECTS | Exploratory Data Analysis
- 3 ECTS | Data Management and Storage
- 6 ECTS | Supervised Machine Learning
- 3 ECTS | Unsupervised Machine Learning
- 3 ECTS | Applications of Machine Learning in Real Cases
Second Semester 30 ECTS
- 6 ECTS | Mathematical Models of Neural Networks
- 3 ECTS | Neural Networks and Deep Learning
- 3 ECTS | Natural Language and Image Processing
- 3 ECTS | Recommender Systems
- 3 ECTS | Applications of Neural Networks in Real Cases
- 6 ECTS | Professional Academic Internships
- 6 ECTS | Master's Final Project
Professors
| Profesores Professors | Porcentaje de Doctores Percentage of PhD holders |
| 28 | 70% |
Javier Sánchez Sierra
Director del Máster en Ingeniería Industrial
Director of the Master’s Degree in Industrial Engineering
Antonio Alcocer Fernández-Pinilla
Profesor del área de Empresa
Professor of the Business area
Jesús Alonso Barriuso
Profesor del área de Procesos Industriales
Professor of the area of Industrial Processes
Roberto Álvarez Fernández
Director del Departamento Escuela de Ingeniería IndustrialDirector de Trabajos Fin de Máster Director of the School of Industrial Engineering Department
Director of Master's Thesis
Alberto Aniz Lecuona
Profesor del área de Ingeniería Eléctrica y Electrónica
Professor of the area of Electrical and Electronic Engineering
Juan Carlos Arroyo Portero
Director de la Escuela Politécnica SuperiorDirector de Trabajos Fin de Máster Director of the Polytechnic School
Director of Master's Thesis
Francisco Badea Romero
Profesor del área de Ingeniería Mecánica
Professor of the Mechanical Engineering area
Rafael Barea del Cerro
Coordinador del programa de doctoradoProfesor de las áreas de Materiales y Procesos Industriales
Director de Trabajos Fin de Máster Coordinator of the doctoral program
Professor of the areas of Materials and Industrial Processes
Director of Master's Thesis
Patricia Benítez Hernández
Profesora del área de EstructurasDirectora de Trabajos Fin de Máster Professor of the area of Structures
Director of Final Master's Projects
Jesús Briones Delgado
Profesor del área de EmpresaDirector de Trabajos Fin de Máster Professor of the Business area
Director of Final Master's Projects
Juan José Coble Castro
Coordinador del área de FísicaProfesor de las áreas de Energía y Medio Ambiente
Director de Trabajos Fin de Máster Coordinator of the Physics area
Professor of the areas of Energy and Environment
Director of Final Master Projects
Sergio Corbera Caraballo
Coordinador del área de Automóvil y MecánicaProfesor del área de Expresión Gráfica
Director de Trabajos Fin de Máster Coordinator of the Automobile and Mechanics area
Teacher of the Graphic Expression area
Director of Final Master's Projects
Fernando Chavarri Dicenta
Profesor del área de Empresa
Professor of the Company area
Juan de Norverto Moríñigo
Profesor del área de Ingeniería Mecánica y de Proyectos
Professor of the area of Mechanical Engineering and Projects
María Rosario Elvira Lavilla
Profesora del área de Química
Professor of the Chemistry area
Luis García Cervantes
Profesor del área de Ingeniería Eléctrica y Electrónica
Professor of the area of Electrical and Electronic Engineering
Francisco Javier García De La Hera
Profesor del área de Estructuras
Professor of the Structures area
Javier García Martín
Profesor del área de Ingeniería Eléctrica y Electrónica
Professor of Electrical and Electronic Engineering
Jesús Guzmán Mínguez
Profesor de las áreas de Química y de Materiales
Professor of the areas of Chemistry and Materials
Ingo Kaiser
Profesor del área de Fundamentos de la Física
Professor of the Fundamentals of Physics area
José Luis Morato Gómez
Profesor del área de Organización y Gestión de la Producción.
Professor of the area of Organization and Management of Production.
Javier Ontañón Ruiz
Profesor del área de Ingeniería Eléctrica y Electrónica
Professor of the area of Electrical and Electronic Engineering
Miguel Ángel Reyes Belmonte
Coordinador y profesor de las áreas de Fundamentos de la Física y de Energía
Coordinator and professor of the areas of Fundamentals of Physics and Energy
Roberto Rodríguez Delgado
Profesor del área de Estructuras
Professor of the Structures area
Antonio Santos Escobar
Profesor del área de Estructuras
Professor of the Structures area
Jesús Vicente López
Profesor del área de Ingeniería Eléctrica y Electrónica
Professor of the area of Electrical and Electronic Engineering
Juan Viguri Flores
Coordinador y Profesor del área de EmpresaDirector de Trabajos Fin de Máster Coordiandor y Professor of the Business area
Director of Final Master's Projects
Gloria Zarzuelo Puch
Profesora de las áreas de Energía y Medio Ambiente
Professor in the areas of Energy and Environment
More Academic Information
Competences
- establish the necessary tasks and the technical profiles that must be part of the team.
- C2: Apply the knowledge, skills and competences acquired in the Master's degree to develop, present and publicly defend before a tribunal an individual project in the area of Data Science.
- C3: Identify and evaluate which product/process/service data can add value to the business. Identify what product/process/service data can be collected, in order to detect what improvements and benefits their treatment can bring to the business.
- C4: Implement in a professional environment the knowledge, skills and competences acquired in the Master's subjects.
- C5: Validate learning models using data sets that include characteristics and objective variables that are consistent with the problem to be solved. Design and create data sets that include characteristics and objective variables that are consistent with the problem to be solved.
- C6: Design and implement mechanisms to capture data from different sources (web, repositories, applications) using various mechanisms: queries, API, scrapping, etc.
- C7: Act with the ethical and legal principles necessary for correct handling of data and application of models, according to the scope of each application.
- C8: Evaluate the data flow and determine the necessary infrastructure for the automatic deployment of the models in production.
- C9: Evaluate optimization techniques to maximize or minimize functions, which are essential in problem modeling and machine learning.
Online Study
Awards to Global Campus Nebrija
Admission
Admission requirementsThose interested in studying and obtaining the Master's Degree in Data Science from Nebrija University must meet the requirements set forth in current legislation, the required admission profile being that of a university graduate -or equivalent- in Mathematics, Physics, Engineering (computer science, industrial technologies, mechanics, automotive, telecommunications, industrial and automatic electronics, aerospace, industrial design and product development, bioinformatics, biotechnology, biomedical, software, computers, multimedia).
For the purposes of pre-admission and admission, the evaluation of the candidate will be made from 0 to 10 points taking into account the following criteria and percentages:
- Academic record [50%]: The grades obtained by the candidate in their previous studies will be assessed.
- Structured personal interview [30%]: The suitability of candidates will be assessed by virtue of their experience, knowledge, technical and professional skills required to successfully complete the studies they intend to take. Their motivation and attitudes will also be assessed, as well as other personal aspects that contribute to their adequate adjustment to the chosen studies. The interview will be conducted in Spanish, since it is the language in which the studies are taught.
- Presentation document of the candidate [20%]: In a personally-prepared document, candidates will explain their motivation and interest in the requested studies, as well as any other personal circumstance that they consider relevant for the selection process.
The admission process will be carried out by the University's Development Department (DDU), which has university advisors who assist candidates during the admission process. The personal interview will be conducted by the Program Director.
In the event that candidates' mother tongue is not Spanish, they must prove a level equivalent to a B2 level (Common European Framework of Reference for Languages, CEFR) of Spanish, through any accredited certificate.
The admission criteria must be assessed within a global strategy aimed at knowing the characteristics of the applicants, in order to determine if the candidate has sufficient motivation, as well as training and knowledge, skills, aptitudes, communication skills, extracurricular activities and future interests necessary to be admitted as a candidate in the curricula of Nebrija University.
Employability
Career Opportunities
The following positions stand out as job opportunities:
Professional internships
Some of the companies and institutions with a collaboration agreement for professional internships are:
More Information on Internships in CompaniesUniversity Life in Data Science
Visit all the Activities of the Higher Polytechnic School
Mathematics and Physics in the digital age
A session in which the challenges and opportunities of mathematicians and physicists in the digital age, interdisciplinarity, innovation and technology were addressed, as well as the bachelor's degrees in Applied Mathematics and Applied Physics (and its double degrees) launched by the Higher Polytechnic School of Nebrija University.
Nebrija Quantum Connection
In order to reinforce its contribution to the educational field and its commitment to students, Nebrija organized the Nebrija Quantum Connection event, which was attended by numerous Quantum Computing experts in Spain such as INDRA, LANTIK, Amazon, Miltiverse, Quasar, BBVAl, ATOS and QUSIDE, in order to promote its dissemination and present the state of this sector in our country.
3rd Edition of Smart Campus
Conference on good teaching practices in digital education Smart Campus 2022, organized by Global Campus Nebrija, with the aim of opening space for dialogue between professionals and sharing experiences regarding challenges in digital education.
Opening ceremony of the academic year
Opening Ceremony for the academic year at the Madrid-Princesa Campus of Nebrija University
Talk by Gabriel López Serrano, Director of Regulatory Affairs for Microsoft, at Nebrija University
The data handled by Artificial Intelligence are "the basis of the future economy," according to Gabriel López Serrano, from Microsoft, at Nebrija University.
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