Graduate School of Engineering and Basic Sciences
- Direction
- Prof. Juan Miguel Marín Diazaraque
- Deputy Direction
- Prof. Eduardo García Portugués, Prof. Stefano Cabras
- Language
- English
- Attendance
- On-campus
- Credits
- 60 ECTS
- Campus
- Madrid - Puerta de Toledo
- Applications
-
☛ Places available: 40
- Departments
- Department of Statistics, Department of Mathematics, Department of Computer Science and Engineering
MORE INFORMATION HERE
For more information click on the link and contact us
APPLICATION FOR ADMISSION
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- Inicio
Statistics, data, analytics. Three words that are shaping the future. Three topics in which you will become proficient in this master.
This master program provides a thorough training in the statistical toolbox behind Data Science. Deep understanding of fundamental statistical methods is emphasized throughout a combination of methodological exposition, computational implementation, and application of methods. Our target is to create self-sufficient data scientists able to tackle any modelling task by applying, modifying/developing, and deploying new data analysis techniques.
Most of the data science masters focus on applications of methods, i.e. on the how to apply, rather than on the statistical techniques behind them: the how to build. The defining characteristic of this master is that it provides the same weight to both components that define the all-terrain data scientist.
The master graduates will have the adequate training at the right time for this new exciting market. Additionally, top master students will have the opportunity to enter the PhD program in Statistics.
│MASTER IN NUMBERS
- ☛ The job market for data scientists has been rapidly growing in the last years and it is expected to grow even more in the future.
- ☛ IBM projects an increment of 28% of the demand of data scientists by 2020 and reports that a 39% of data scientist positions require a master or a PhD.
- CURRICULUM
- CURRICULUM
This is a one academic year master (60 ECTS) offered in English. It is comprised by 39 ECTS of compulsory subjects, 15 ECTS of electives and a Master’s Thesis of 6 ECTS.
The master offers two pathways according to the future student professional interests: either mainly methodological or mainly applied. The first one places more emphasis in advanced statistical methods for data science, while the latter is adequate for those more interested in applications, consulting, and high-performance computing.
Each pathway is associated to five out of ten elective subjects:- Methodological: Simulation and Resampling, Time Series Analysis; Advanced Regression and Prediction, Biostatistics; Functional Data Analysis.
- Applied: Data Tidying and Reporting; Scalable and Distributed Computing; Network Analysis, Graphical and Hidden Markov Models; Advanced Numerical Methods for Data Science.
Course 1 - Semester 1
1st Term Subjects ECTS TYPE Language Mathematics for Data Science 3 C 
Probability 3 C Statistical Inference 3 C Programming in R 3 C Numerical Methods for Data Science 3 C 2nd Term Subjects ECTS TYPE Language Stochastic Processes 3 C Multivariate Analysis 3 C Statistical Learning 3 C Regression Models 3 C Advanced Programming 3 C Course 1 - Semester 2
3rd Term Subjects ECTS TYPE Language Bayesian Inference 3 C Nonparametric Statistics 3 C Perspectives on Statistics 3 C Choose 2 electives Simulation and Resampling 3 E Time Series Analysis 3 E Data Tidying and Reporting 3 E Scalable and Distributed Computing 3 E 4th Term Subjects ECTS TYPE Language Choose 3 electives Advanced Regression and Prediction 3 E Biostatistics 3 E Network Analysis 3 E Graphical and Hidden Markov Models 3 E Functional Data Analysis 3 E Advanced Numerical Methods for Data Science 3 E Course 1 - Annual
Master's Thesis Subjects ECTS TYPE Master's Thesis 6 MT C) Compulsory: 39 ECTS
E) Elective course: 15 ECTS
MT) Master's Thesis: 6 ECTS
course Programs
- QUALITY
GENERAL COURSE INFORMATION
☛ First year offered: 2018
QUALITY INDICATORS
PROGRAMME’S QUALITY ASSURANCE
The Academic Committee of the Master’s programme complies with the SGIC-UC3M and it is responsible for the follow-up, analysis, review, assessment and quality of the program, it contributes with proposals to improve the program and produces the “Memoria Académica de Titulación” (Programme Report).
Graduate Profile and Competences
- CURRICULUM
- FACULTY
CARLOS III UNIVERSITY OF MADRID (UC3M) FACULTY
- AGUILERA MORILLO, MARÍA DEL CARMEN
Departament of Statistics
Assistant Professor
PhD
Brief CV
- ALER MUR, RICARDO
Department of Computer Science and Engineering
Associate Profesor
PhD
Brief CV
- ARRIBAS GIL, ANA
Departament of Statistics
Postdoc
PhD
Brief CV
- CABRAS, STEFANO
Departament of Statistics
Associate Professor
PhD
Brief CV
- CARRETERO PÉREZ, JESÚS
Department of Computer Science and Engineering
Full Professor
PhD
Brief CV
- CASCOS FERNÁNDEZ, IGNACIO
Departament of Statistics
Associate Professor
PhD
Brief CV
- D'AURIA, BERNARDO
Departament of Statistics
Associate Professor
PhD
Brief CV
- DELGADO GOMEZ, DAVID
Departament of Statistics
Associate Professor
PhD
Brief CV
- DURBÁN REGUERA, MARÍA LUZ
Departament of Statistics
Full Professor
PhD
Brief CV
- GALEANO SAN MIGUEL, PEDRO
Departament of Statistics
Associate Professor
PhD
Brief CV
- GARCÍA PORTUGUÉS, EDUARDO
Departament of Statistics
Assistant Professor
PhD
Brief CV
- KAISER REMIRO, REGINA
Departament of Statistics
Associate Professor
PhD
Brief CV
- MARÍN DIAZARAQUE, JUAN MIGUEL
Departament of Statistics
Associate Professor
PhD
Brief CV
- MOLINA PERALTA, ISABEL
Departament of Statistics
Associate Professor
PhD
Brief CV
- NIÑO MORA, JOSE
Departament of Statistics
Full Professor
PhD
Brief CV
- NOGALES MARTÍN, FRANCISCO JAVIER
Departament of Statistics
Associate Professor
PhD
Brief CV
- RUIZ MORA, CARLOS
Departament of Statistics
Associate Professor
PhD
Brief CV
- TERAN VERGARA, FERNANDO DE
Departament of Mathematics
Associate Professor
PhD
Brief CV
- WIPER, MICHAEL PETER
Departament of Statistics
Associate Professor
PhD
Brief CV
- AGUILERA MORILLO, MARÍA DEL CARMEN
- ADMISSION
- ADMISSION
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:
REQUIREMENTS
According to the regulations established by Royal Decree 1393/2007, as amended by Royal Decree 861/2010, It is required that students are in possession of a previous university qualification (at least Bachelor's degree or equivalent), preferably in the training areas of:
- Statistics
- Mathematical sciences
- Physical sciences
- Informatics engineering
- Industrial engineering
- Telecommunications engineering
It does not exclude the possibility that graduates of other degrees may access the master's studies as long as they meet the aptitude requirements mentioned in the admission profile, accrediting sufficient levels of knowledge in the areas of Mathematics (Algebra and Calculus), Statistics (Probability and Inference) and Computer Science (basic programming skills).
Previous professional experience is not an essential requirement, although it will be valued positively.
ADMISSION CRITERIA
The student selection will be based on:
ADMISSION CRITERIA WEIGHING Academic record of studies access 50% Professional experience 10% Qualifications obtained in essential subjects to take the master 20% Motivation, interest and letters of recommendation 10% Others: awards, portfolio of works 10% Language requirements
Check the general language requirements required to study a Master’s at UC3M, depending on whether it is in Spanish, English or bilingual.
students with foreign university degrees
Once admitted to the Master’s, students with university degrees issued by a higher education institution belonging to an educational system outside the EHEA, must provide, for enrolment, the diploma, legalized by diplomatic procedures or by means of The Hague Apostille. They must also submit the transcript of records, with the grade point average, duly legalized.
More information about Legalization of Foreign Documents.
If needed, documents must be accompanied by an official sworn translation into Spanish.
- ENROLLMENT
FEES *
2020-2021 Academic year
- Reservation fee: €450 (It will be paid once the student receives notification of admission to the master’s, and deducted from the first tuition payment)
60 ECTS in the first academic year:
- EU students: €4,800 (€80/ECTS credit)
- Non EU students: €7,200 (€120/ECTS credit)
* Pending approval by the Regional Government of Madrid for 2020/2021
NOTE: The enrolment fees do not include the cost of issuing the master’s degree certificate.Additional information
- You may enrol on the master’s degree after completing the admission process and receiving formal confirmation of your acceptance.
- When performing the enrolment you can choose between Full-time enrolment or Part-time enrolment.
- The email address provided upon enrolment will be used for formal communications; students are therefore kindly requested to check their mail regularly.
- Pursuant to the regulations of the Universidad Carlos III de Madrid, a student failing to pay any part of the fees will not be admitted and the enrolment process will be terminated. In cases of cancellation of enrolment due to non-payment, the University may demand the payment of the pending amounts for enrolment in previous academic courses as a prior condition of enrolment.
No diploma or certificate will be issued if a student has any outstanding payments.
Best Practices and Regulations
- ADMISSION
- SCHOLARSHIPS
EXCELLENCE AWARDS 2019–2020
The Master in Statistics for Data Science offers an specific program of grants to boost and promote the excellence in the academic performance during the master. This translates to 6 awards, with a total amount of 7000€, to be awarded at the end of the academic course to those students with the most outstanding academic records.
The breakdown of the awards is as follows:
- First award (1 award in total):
- Requirements: have the most outstanding academic record and an average grade greater or equal to 9,00.
- Amount: 2800€.
- Second awards (2 awards in total):
- Requirements: have one of the three most outstanding academic records with an average grade greater or equal to 8,50 and do not receive a higher award.
- Amount: 1200€.
- Third awards (3 awards in total):
- Requirements: have one of the six most outstanding academic records with an average grade greater or equal to 8,00 and do not receive a higher award.
- Amount: 600€.
RULES
- The awards may be declared null and void if no applicant met the required average grade.
- The awards will be specified as a reduction in the tuition fees, understanding these as the net tuition fees that were not subjected to previous exemptions. The amount of the awards will never be above the net tuition fees.
- Only the students that defended the Master’s Thesis during the current academic course may receive the awards.
- The average grade will be computed with weighting of the call in which each of the subjects was exceeded, according to the specifications given in the “Resolución del Rector de fecha 1 de octubre de 2014, relativa al procedimiento de determinación de la nota media del expediente de los alumnos de la Universidad Carlos III de Madrid”.
- The computation of the average grade will be made at the end of the academic course, after the defense of the master’s theses in September takes place.
- In the presence of a draw, priority will be given to the higher amount of “matrículas de honor”, “sobresalientes”, “notables” y “aprobados” in the academic record, successively. If the draw prevails, the academic commission of the master will examine the draw and take a decision.
- If there is any ambiguity in the English version of this document, the interpretation of its Spanish version will prevail.
EXCELLENCE AWARDS 2018–2019
The excellence awards for the course 2018-2019 have been communicated to the awarded students as of the 25th of November 2019. One first award, two second awards, and one third award were conceded.
General information on grants and scholarships
For more information on specific grants of interest awarded by UC3M and by other agencies or organisations.
- PRACTICAL INFORMATION