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Home   >  Master's & postgraduate courses  >  Education  >  Postgraduate course in Data Science for Mobility and Transport
We advise you! Request information or admission

Presentation

Edition
1st
Credits
15 ECTS (126 teaching hours)
Delivery method
Live online
Language of instruction
Spanish
Fee
€3,350
Special conditions on payment of enrolment fee and 0,7% campaign

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Registration open until the beginning of the programme or until end of vacancies.
Dates
Classes start: 04/11/2026
Classes end: 28/05/2027
Programme ends : 04/06/2027
Class schedule
Wednesday: 6:00 pm to 9:00 pm
Thursday: 6:00 pm to 9:00 pm
Why this programme?
The digital transformation of the mobility sector is generating ever-increasing amounts of data from sensors, vehicles, transportation systems, surveys, and other sources. Understanding how to interpret this data is key to analysing mobility, supporting transportation planning, and making evidence-based decisions. Likewise, many organizations need technical professionals capable of transforming available data into rigorous and actionable analysis.

The Postgraduate Program in Data Science for Mobility and Transportation prepares you to apply data processing, analysis, and modelling techniques to real-world mobility and transportation problems. You will learn to work directly with datasets, clean and impute data, detect outliers, analyse spatiotemporal data, and apply statistical and machine learning techniques using tools such as R, RStudio, Python, and SQL.

Its main distinguishing feature is its practical, hands-on approach: you will not only learn about the applications of Data Science in mobility, but you will also learn to work directly with them. You will have access to teaching staff with extensive experience in transport modeling, data analytics, Smart Mobility and projects with public bodies and companies, and you will apply the knowledge acquired in a final data-based project.
Aims
Upon completion of this postgraduate program, you will be able to:
  • Identify, obtain, and prepare mobility and transportation data from various sources and formats.
  • Clean, transform, and validate datasets, applying imputation techniques and detecting errors and outliers.
  • Analyse mobility data using statistical, multivariate, and machine learning techniques.
  • Formulate mobility and transportation problems as data analysis problems and select the most appropriate techniques for addressing them.
  • Apply programming and data processing tools such as R, RStudio, Python, and SQL to cases related to mobility and transportation.
  • Develop data analysis solutions applied to real-world mobility and transportation problems, working practically with datasets and projects.
Who is it for?
This postgraduate program is primarily aimed at technical professionals and university graduates in engineering and computer science who wish to develop advanced skills in data processing and analysis applied to mobility and transport:
  • Civil Engineers, Industrial Engineers, Computer Scientists, and other graduates in technical fields.
  • Transportation, mobility, and infrastructure professionals who want to deepen their knowledge of data processing and analysis.
  • Mobility consulting and engineering professionals involved in transport planning or modeling.
  • Information technology, data analytics, and Big Data professionals interested in specializing in mobility and transport.
  • Logistics and Intelligent Transportation Systems (ITS) professionals who work with data to support decision-making.
  • Research and development professionals who wish to apply Data Science techniques to real-world mobility and transport problems.
Prerequisites: Programming knowledge in a language such as C, Fortran, or Java is required, as well as knowledge of SQL and basic database concepts. Basic knowledge of a statistical package, linear algebra (operations with matrices and vectors) and written comprehension of technical English related to the field of statistics and operations research is recommended.

Training Content

List of subjects
1 ECTS 10h
Introduction to Transport, Mobility and Logistics Data
  • Introduction to transport data sources and their use in planning and simulation models.
  • Description, classification and typology of transport systems.
  • Purposes and uses of data collection.
  • Classification of traditional and ICT-based data sources.
  • Equity and effects of digitalization on mobility.
  • Data collection through surveys.
  • Main types of transport and mobility surveys.
  • Data exploitation and case studies.
4 ECTS 30h
Data Management
  • Relational and SQL data management.
  • Management of large amounts of data and data in semi-structured or unstructured formats.
  • Relational database extensions.
  • Big data technologies for managing spatiotemporal and mobile data.
4 ECTS 30h
Multivariate Analysis Methods and Tools Applied to Mobility
  • Multiple linear regression. Use of categorical variables in modelling.
  • Generalized linear models. Binary response (logit models) and count response (Poisson models).
  • Hands-on. Tools in RStudio and the car package.
2 ECTS 20h
Elements of Data Analytics in Mobility Modelling
  • Structure, nature, and role of data used in passenger transport and logistics models, and in both traditional and emerging transport systems and networks.
  • Main machine learning methods successfully used in transport applications.
  • Real-world case studies along with the application of these methods to different datasets.
1 ECTS 10h
Study cases. Summary of Applications
  • Real-world case studies involving large volumes of data, data mining, and optimization modeling.
  • Estimation of dynamic origin-destination (OD) matrices from GPS data and traffic counts.
  • Urban Freight Distribution Problem: 2 - Echelon.
3 ECTS 26h
Data Science Project for Mobility and Transport
  • Problem identification (in the field of data analytics for mobility).
  • Proposal of a rigorous technical solution.
  • Development of a prototype to validate the technical proposal.
An example of the application of this approach is the project:
Predicting mobility flows using AI
How can mobility demand between zones be anticipated? This project uses socioeconomic data and machine learning techniques to predict travel flows, comparing neural networks and SVR models to achieve more accurate predictions.
Degree
University-specific Expert Diploma in Data Science for Mobility and Transport, Issued by the Universitat Politècnica de Catalunya. Issued in accordance with the provisions of Article 7.1 of Organic Law 2/2023, of 22 March, on the University System; Article 36 of Royal Decree 822/2021, of 28 September, which establishes the organisation of university education and the procedure for quality assurance; and Articles 2 and 8 of the Amendment to the Regulations for Continuing Education Programmes, approved by Agreement CG/2025/02/35, of 25 March, of the Governing Council of the UPC. To obtain this qualification, it is necessary to hold a prior university degree equivalent to level 2 of the Spanish Qualifications Framework for Higher Education (MECES). Otherwise, the student will receive a certificate of completion of the programme issued by the Fundació Politècnica de Catalunya. (See details appearing on the certificate).

Learning methodology

The teaching methodology of the programme facilitates the student's learning and the achievement of the necessary competences.

The training combines conceptual foundations with practical application of knowledge, promoting active student participation and work on situations and problems related to mobility and transport. Throughout the program, students have different spaces to apply the tools and knowledge acquired, analyse cases, solve problems and compare their results with teachers and the rest of the participants.

The development of the final project allows the integration of the knowledge worked on during the program into a practical group task, with the support of teachers and specific theoretical sessions depending on the needs of the project. The final presentation encourages the exchange of ideas and results between the different groups.


Learning tools
Participatory lectures
A presentation of the conceptual foundations of the content to be taught, promoting interaction with the students to guide them in their learning of the different contents and the development of the established competences.
Practical classroom sessions
Knowledge is applied to a real or hypothetical environment, where specific aspects are identified and worked on to facilitate understanding, with the support from teaching staff.
Solving exercises
Solutions are worked on by practising routines, applying formulas and algorithms, and procedures are followed for transforming the available information and interpreting the results.
Case studies
Real or hypothetical situations are presented in which the students, in a completely participatory and practical way, examine the situation, consider the various hypotheses and share their own conclusions.
Tutorship
Students are given technical support in the preparation of the final project, according to their specialisation and the subject matter of the project.
Assessment criteria
Attendance
At least 80% attendance of teaching hours is required.
Level of participation
The student's active contribution to the various activities offered by the teaching team is assessed.
Solving exercises, questionnaires or exams
Individual tests aimed at assessing the degree of learning and the acquisition of competences.
Completion and presentation of the final project
Individual or group projects in which the contents taught in the programme are applied. The project can be based on real cases and include the identification of a problem, the design of the solution, its implementation or a business plan. The project will be presented and defended in public.
Work placements & employment service
Students can access job offers in their field of specialisation on the My_Tech_Space virtual campus. Applications made from this site will be treated confidentially. Hundreds of offers of the UPC School of Professional & Executive Development employment service appear annually. The offers range from formal contracts to work placement agreements.
Virtual campus
The students on this postgraduate course will have access to the My_ Tech_Space virtual campus - an effective platform for work and communication between the programme's students, lecturers, directors and coordinators. My_Tech_Space provides the documentation for each training session before it starts, and enables students to work as a team, consult lecturers, check notes, etc.

Teaching team

Academic management
  • Montero Mercadé, Lídia
    info
    View profile in futur.upc / View profile in Linkedin
    PhD in Computer Science from the Technical University of Catalonia (UPC). Degree in Computer Science from the FIB-UPC. Professor of Statistics and Operations Research at the UPC since 1998. She teaches on the Master's Degree in Supply Chain, Transport and Mobility at the UPC. Senior Consultant at Advanced Logistics Group (SANO). Experience of more than 25 years in simulation and modelling of problems in public and private transport networks. Transport analytics (data science applied to mobility and transport data) and modelling of transport demand. Collaborator with inLab-UPC.
Teaching staff
  • Barceló Bugeda, Jaume
    info
    View profile in Orcid
    Doctor in Physical Sciences from the Autonomous University of Barcelona (UAB). Professor of the Department of Statistics and Operations Research at the Universitat Politèctica de Catalunya (UPC), teaching at the Barcelona School of Informatics (FIB) and the Faculty of Mathematics and Statistics (FME) at the UPC until 2014. Professor Emeritus of the UPC. Specializing in Transport Systems and the applications of optimization and simulation models for the analysis of transport systems. Author of more than 140 articles published in indexed journals, conference proceedings and books.
  • Codina Sancho, Esteve
    info
    View profile in futur.upc
    Industrial Engineer for the ETSEIB of Barcelona at 1984 (UPC). Doctor Industrial Engineer for the UPC at 1994 with Extraordinary prize. Teacher of the Department of Statistics and Operative Research (DEIO) of the UPC since 1991, and Titular of University since 2006. Expert at Operative Research, Mathematical Programming, Sciences of the Transports, predominately at motifs of planning and modelling
  • Jovanovic, Petar
    info
    View profile in futur.upc
    PhD in Computer Science from the Polythecnic University of Catalonia (UPC) and Université Libre de Bruxelles. MSc in Computer Science from the UPC. BSc in Software Engineering from University of Belgrade. His research is in the area of Business Intelligence, big data Management systems and distributed databases.
  • Montero Mercadé, Lídia
    info
    View profile in futur.upc / View profile in Linkedin
    PhD in Computer Science from the Technical University of Catalonia (UPC). Degree in Computer Science from the FIB-UPC. Professor of Statistics and Operations Research at the UPC since 1998. She teaches on the Master's Degree in Supply Chain, Transport and Mobility at the UPC. Senior Consultant at Advanced Logistics Group (SANO). Experience of more than 25 years in simulation and modelling of problems in public and private transport networks. Transport analytics (data science applied to mobility and transport data) and modelling of transport demand. Collaborator with inLab-UPC.

Career opportunities

  • Mobility and transport data specialist or analyst in consulting, engineering, R&D and technology companies.
  • Transport planning, modelling and simulation technician, applying data analysis techniques to mobility systems.
  • Mobility and transport consultant, supporting decision-making through data analysis and exploitation.
  • Data analytics and Big Data specialist applied to mobility, transport and logistics.
  • Technician or analyst in public bodies and administrations linked to mobility and transport planning and management.
  • R&D and Smart Mobility professional, developing data-based solutions for real mobility and transport problems.

Request information or admission

Information and guidance:
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Programme: Data Science for Mobility and Transport

Fee: €3,350

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How to start admission
To start the enrolment process for this programme you must complete and send the form that you will find at the bottom of these lines.

Next you will receive a welcome email detailing the three steps necessary to formalize the enrolment procedure:

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3. Pay €110 in concept of the registration fee for the programme. This fee will be discounted from the total enrolment fee and will only be returned when a student isn't admitted on a programme.

Once the fee has been paid and we have all your documentation, we will assess your candidacy and, if you are admitted on the course, we will send you a letter of acceptance. This document will provide you with all the necessary information to formalize the enrolment process for the programme.





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ENROLMENT CONDITIONS OF THE FUNDACIÓ POLITÈCNICA DE CATALUNYA

Introduction

The Fundació Politècnica de Catalunya (FPC), with tax identification number G60664000, registered in the Register of Foundations of the Government of Catalonia under no. 834, designs, promotes and manages the continuing education programmes of the Universitat Politècnica de Catalunya (UPC), as well as other training activities it promotes. The academic regulation of the UPC's continuing education programmes is set out in Agreement CG/2025/02/35, of 25 March, of the Consell de Govern, which approves the update of the amendment to the regulations governing continuing education programmes. And Articles 36 and 37 of Royal Decree 822/2021, of 28 September, which establishes the organisation of university education and the procedure for ensuring its quality. The UPC Social Council approves the price of continuing education programmes, as well as discounts, grants and ancillary services for each academic year.


Provision, knowledge and acceptance of the Enrolment Conditions

Reading and accepting these Enrolment Conditions is an essential requirement for studying at the FPC, as they constitute the basis of the training services contract that participants sign electronically with the FPC. These Enrolment Conditions are available to users on the Transparency Portal: https://www.fpc.upc.edu/cat/fpctransparent/normativa/. These Conditions are applicable to all courses taught by the FPC, with the exception of those aimed at other university institutions and public and private entities, which shall be governed by the legal instruments binding on the participating institutions.


Admission and registration fees

The admission process may require the advance payment of registration fees; this amount will be deducted from the tuition fee once admitted and will only be refunded in the event of non-admission, deferral or non-completion of the course, in the latter case, only if the letter of admission is valid. The admission process concludes with the sending of the admission letter to the participant, which includes the details of the course, the period of study, the tuition fees and the payment deadlines.


Enrolment

The enrolment process is formalised with the first payment of the course fee, whether partial or total. Therefore, this first payment of the course fee corresponds to the signing of the contract for the provision of training services regulated in these Conditions, regardless of whether the total price or any of the agreed payment instalments have been paid in full.

It is the participant's responsibility to find out about discounts on the enrolment fee and to prove that they meet the relevant criteria to benefit from them, always prior to formalising their enrolment; otherwise, they will not be able to benefit from them. Discounts and grants cannot be combined, unless they are not incompatible and this is expressly stated.

The participant declares that they are aware of and accept the calls for applications and the terms and conditions of the financial aid corresponding to the current academic year for which they have applied to be a beneficiary. If the student does not complete or withdraws from the course for which they have received aid, a discount or a grant within the period specified in the corresponding call for applications or in the enrolment document, they must return the amount granted or deducted from the price to the FPC. The provisions of the section on Changes to enrolment in these conditions shall not apply to this participant.

Enrolment is personal and non-transferable, so that once formalised, it shall only entitle the natural person who has been identified as a candidate and, subsequently, as an admitted person to undertake the course of study.

The enrolment fee may be paid in full or in part by third parties, although the right/obligation to follow the training course corresponds to the participant, without the paying party being able to interfere with or prevent the exercise of this right in any way. The foregoing is without prejudice to the FPC's right to prevent the participant from continuing in the cases provided for in the section on Non-payment of the enrolment fee provided for in these Conditions.

The amount paid for enrolment will not be refunded once the study has begun, nor after 14 calendar days from the date of payment. Otherwise, the right of withdrawal may be exercised. The amount paid will only be refunded if the study is postponed or does not take place.

Notwithstanding the above, and on an exceptional basis, a tuition fee refund will be issued if the following circumstances apply:

  • Visa refusal
    • For courses starting in-person: proof must be provided in the form of the refusal letter, and the refund must be requested within a maximum of 15 days following the start of the course; the refund will be in full.
    • For courses starting online and ending in person: proof must be provided in the form of the refusal letter, always before the in-person start of the course, and the refund will be proportional to the credits not taken.
  • Serious illness or accident affecting the participant: proof must be provided in the form of an official medical certificate, stating the start date of the illness and the expected period of convalescence. If this occurs before the start of the course, a full refund will be issued. If this occurs after the start of the course, the refund will be proportional to the credits not taken.

In both cases only, the FPC will refund, as appropriate, the total or proportional amount paid by the participant, minus €300 to cover the costs of processing the academic record.


Subsidised training

The FPC is not responsible for fulfilling the academic and/or administrative requirements for the contracted training to be subsidised. The participant or the person paying for the training does so at their own risk and exempts the FPC from any liability or compensation.


Change of enrolment

Requests to change enrolment, whether in terms of study or teaching method, must be made within 15 calendar days of the start date of the original course. Requests made after this period will not be accepted. The request will be assessed and its suitability determined on a case-by-case basis. When the change involves an increase in the total enrolment fee, the participant will be responsible for the difference. When the change involves a decrease in the enrolment fee, the difference will be refunded. Once evaluated, and regardless of the outcome of the request, changes to enrolment will incur a cost of €300 for the applicant for the processing of academic records, unless the change is due to causes attributable to the FPC.


Refund of tuition fees

The FPC reserves the right to cancel or postpone a study due to a lack of participants. Affected participants may choose between participating in another study or requesting a refund of the amount paid within one month of notification by the FPC. If no response is received, the amount paid will be used to support other students. The FPC will not provide any additional compensation and/or indemnification in the event of cancellation or postponement of a study programme or changes in its delivery. In the event that the FPC makes changes that do not substantially affect the content of the study programme, the place of delivery, the timetable and/or the start date, the participant will not be entitled to a refund of the registration fee or any additional compensation.


Non-payment of tuition fees

Failure to pay the total or partial amount of the tuition fees within the established deadlines may result in the suspension or termination of the training service under the terms indicated below. The FPC is authorised to take whatever action it deems appropriate to suspend the service; on the one hand, in the academic sphere, by suspending the academic record, denying access to teaching in the classroom (face-to-face or online), limiting access to the virtual campus, not assessing any of the subjects and making it impossible to continue with internship agreements, among other measures; and on the other hand, in the administrative and legal sphere, by undertaking the corresponding claims and actions for compensation.

Students who have outstanding debts with the FPC or who have not passed all the credits necessary to complete their studies before the end date of the course will not be able to obtain their degree or certificate, as applicable. Individuals with outstanding amounts payable to the FPC will not be able to enrol in any new studies offered by the FPC until the outstanding amount has been paid.

Finally, the FPC reserves the right to permanently suspend enrolment (automatic withdrawal), without any obligation to refund any amount, in the following cases:

  • Lack of accuracy and/or validity of the information and documentation provided and failure to respond to documentation requirements;
  • Non-payment of part or all of the enrolment fee within the agreed deadlines;
  • Engaging in any behaviour, expression or content that is defamatory, illegal, offensive or that undermines the values and dignity of individuals (teachers, participants, management staff, etc.) or the good image and reputation of the FPC, whether in physical or virtual environments, including social networks.

Right of withdrawal

Participants in a study may exercise their right of withdrawal for a period of 14 calendar days from the date of enrolment, provided that the study has not yet begun. Therefore, by reading and accepting these Terms and Conditions, participants are informed that once the course has begun or is in progress, the right of withdrawal no longer applies, in accordance with the provisions of Article 103 a) of Law 3/2014 of 27 March, which amends the revised text of the General Law for the Defence of Consumers and Users and other complementary laws, approved by Royal Legislative Decree 1/2007 of 16 November, and related regulations.


Teaching

The place and/or date of teaching may change for academic reasons (changes and adjustments to the calendar, need for additional teaching resources, etc.) and for organisational and logistical reasons (adaptation of spaces). Participants will be notified of any such changes at least 15 calendar days before the start of the course. Specific and temporary changes will be notified in advance.


Right to a degree/certificate

Upon completion of a continuing education master's degree, specialisation diploma or expertise diploma, students are entitled to receive a degree, issued by the rector of the University, for students with a previous university degree equivalent to level 2 of the Spanish Qualifications Framework for Higher Education (MECES), according to a standardised model. Students who do not provide proof of their university degree are entitled to obtain a certificate from the FPC, in accordance with a standard model. Short courses, with a workload of less than 15 ECTS credits, entitle students to obtain a certificate issued by the FPC, according to a standard model; however, if these courses include so-called micro-accreditations, students will obtain a digital accreditation issued by the University and recognised in the countries participating in Europass or equivalent. Degrees are issued in Catalan and English and, at the student's request, in Spanish and English. In the case of joint degrees, the issuance must comply with the provisions of the corresponding collaboration agreement.


Accreditation of university qualifications and other documents

If the required documentation is not not submitted before the last day of study for those degrees that require it, or if it is not authentic and/or sufficient, the degree will not be issued, even if the participant has passed the course.


Dispute resolution

The training services provided by the FPC are, in all cases, subject to private law. Any interpretation or divergence arising from these Terms and Conditions shall be the responsibility of the FPC. In the event of disagreement, the dispute shall be subject to private law and the courts of the city of Barcelona with ordinary civil jurisdiction, with express waiver of any other jurisdiction that may apply.


Belongings in the event of theft

Neither the FPC nor its staff shall be liable for any loss, damage or theft of any type of personal or similar items carried by participants or other occasional users of the facilities, who must pay special attention to their belongings at all times.


Organisation of teaching in exceptional circumstances

The FPC organises teaching in a flexible environment that allows it to adapt to any unforeseen circumstances that may arise, as well as to any regulations that may be established by the authorities. If at any time the authorities (university, health or any other competent body) recommend limiting face-to-face teaching as much as possible, the FPC, in coordination with these authorities, will take the necessary measures to implement this recommendation, and, as a result, teaching activities may become 100% online during the period established in the relevant recommendation, without the need to declare a state of emergency and/or suspend face-to-face teaching activities and/or implement formal lockdown or mobility restriction measures.


Barcelona, 19 May 2026


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