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Smart Mobility Data Science and Analytics
Data is central to our future and technological advancement. As we continue to urbanise and gather more data about our mobility patterns and urban systems, the challenge is not simply the amount of data, but how we manage it, critically understand its quality, and utilise findings to address our cities’ most pressing challenges. Today, there is an increasing need for a new generation of data scientists capable of exploring our ever-increasing urban data and extracting meaningful insights. Such work is critical to supporting cities’ strategic decisions and pushing us towards a more sustainable future, centred on efficient resource use, a clean environment, equitable citizen engagement, and a healthy, low-carbon society.
The Smart Mobility Data Science and Analytics programme is designed in an interdisciplinary fashion and emphasises new and emerging transportation technologies and services for citizens, goods and logistics. Furthermore, as an EIT Urban Mobility Master School programme, it integrates entrepreneurship and innovation throughout the coursework, specifically designed to train future elite data scientists in urban mobility and innovation.
Programme
MSc Smart Mobility Data Science and Analytics
ECTS
120 ECTS
Duration
Two years, full-time
Language of instruction
English
Partner universities
Start your application
For eligibility, tuition fees & scholarships
How is the programme structured?
All programmes at the EIT Urban Mobility Master School have a unique study path:
- Students study one year each at two different universities, the “entry” university and the “exit” university. All options are located at a leading university in Europe in the field of urban mobility.
- Graduating students will be awarded two officially recognised Master of Science degrees, from each of the two universities. Moreover, the programme is designed so that students may attain the qualifications for a certificate awarded by the European Institute of Innovation and Technology (EIT).
- During the first year of study students will be introduced to innovation and entrepreneurship, and participate in an extended challenge project. During the same year, students will acquire essential technical skills for tackling urban mobility challenges.
- Between the first and second year, students will participate in a Summer School to apply new skills to two different cities within Europe.
- In the second year, students will choose from several more specialised courses to improve technical, as well as innovation and entrepreneurship, proficiencies. Students will also participate in a shorter challenge project that includes an internship at a company or organisation working to meet urban mobility challenges. To complete their degree, in the second year, students will carry out an independent Master’s thesis, combining and demonstrating their full set of technical and entrepreneurial skills.
- Students will graduate with a wide range of career opportunities, within the public and private sector; as well as have the know-how to start their own businesses or conduct rigorous research.
- Students and graduates of the EIT Urban Mobility Master School also have access to programmes and initiatives that support student entrepreneurship.
Who can apply?
The programme welcomes candidates who have a solid foundation in analytical problem solving with an eye for detail, as demonstrated by a bachelor’s degree in Engineering, Computer Science, Information Technology, Software Engineering, Computer Engineering, Information Systems or a related field.
What are the career opportunities?
Graduates of the Smart Mobility Data Science and Analytics programme will receive a degree, as well as training in entrepreneurship and innovation, practical experience in the industry, and a strong network throughout the EU; unlocking incredible opportunities for a career in the world of big mobility data. The skills acquired during the programme are in high demand in all sectors related to mobility and transport, and at private logistics and transport management companies, ride-sharing startups, the automotive sector, and cities and public institutions.
Which diploma will I receive after graduation?
Eindhoven University of Technology: The TU/e Master’s programme leads to a “Master of Science” degree. Students receive an official diploma both in English and in Dutch. The name of the Master’s programme (Architecture, Building and Planning) and the track (Smart Mobility Data Science and Analytics) will also be printed on the diploma.
Ghent University: You will receive a “Master of Science in Industrial Engineering and Operations Research (Transport and Mobility Engineering)” diploma from Ghent University.
Polytechnic University of Catalonia (UPC): Students will receive an official diploma upon successfully completing the “Máster Universitario en Movilidad Urbana / Master in Urban Mobility por la Universidad Politécnica de Catalunya Especialidad en Innovación y Emprendimiento / Innovation and Entrepreneurship”. The major obtained (e.g. Smart Mobility Data Science and Analysis) will be specified in the Supplement to the diploma as an itinerary. The diploma and the supplement will include translation to three languages: Catalan, Spanish, and English.
University of Tartu: Students will receive a Master of Science in Engineering (Computer Science) degree. The diploma will be in Estonian and English.
University of Lisbon-Técnico.IST: Students will receive a Master of Science in Transport System.
Programme
MSc Smart Mobility Data Science and Analytics
ECTS
120 ECTS
Duration
Two years, full-time
Language of instruction
English
Partner universities
Start your application
For eligibility, tuition fees & scholarships
Where can I study Smart Mobility Data Science and Analytics?
The available universities for the Smart Mobility Data Science and Analytics programme are the following:
Eindhoven University of Technology
The SMDA track at Eindhoven University of Technology equips students with the skills to efficiently manage and analyse large mobility datasets. Using an interdisciplinary approach, it focuses on understanding data quality and leveraging it to address complex urban challenges.
Contents at a glance
The curriculum provides students with profound knowledge in advanced statistical expertise to model and forecast mobility patterns, essential for future city planning. Moreover, the curriculum includes 30 ECTS dedicated to innovation and entrepreneurship, distinguishing the SMDSA track in the field of transport-related studies. Through hands-on projects, students apply their knowledge to real-world mobility issues, preparing them to lead as future entrepreneurs in the field.
Matching career profiles
The Eindhoven University of Technology is a great choice for careers in urban planning and transport modeling in the public sector, as well as in start-up environments due to the extensive support for entrepreneurship.
Specific entry year requirements
None except for general EIT Urban Mobility Master School requirements.
Specific exit year requirements
- Strong mathematical foundations, including understanding of linear algebra concepts and applications, proficiency in calculus for mathematical modeling, and knowledge of probability and statistics, including probability laws, distributions, and Bayesian inference
- Programming and software skills with competence in Python programming (including algorithm implementation and object-oriented principles), experience using Matlab and Simulink for computational modeling and simulation, and familiarity with programming methods, data processing, and analysis
- Proficiency in algorithms and data structures, including understanding of structures like graphs and trees, ability to implement both iterative and recursive algorithms, and application of optimization techniques for effective problem-solving
- Solid understanding of logic and set theory, including knowledge of set theory operations, logical reasoning, first-order logic and inference rules such as modus ponens, as well as understanding of Boolean algebra for logical operations
- Practical application of mathematical and programming knowledge in operations management, with a basic understanding of new product development processes and experience addressing transportation problems and inventory control models
Why Eindhoven?
Eindhoven, a thriving center for master’s students, is renowned for its innovation and cutting-edge approach to urban mobility. Known as the “Brainport” of Europe, the city leads in sustainable transport solutions, from smart traffic systems to advanced cycling infrastructure and e-mobility initiatives. With its forward-thinking culture, collaborative tech ecosystem, and vibrant student community, Eindhoven offers an ideal environment for academic excellence and exploring the future of urban mobility.
University of Tartu
The SMDSA track at the University of Tartu teaches basic data science skills, especially tailored for business in the mobility sector.
Contents at a glance
The curriculum trains students to design and manage solutions for the challenges and issues faced by modern cities and large companies. The courses cover the entire data life cycle and integrates digital humanities and social sciences, enabling analysis across various. Aside from the computer science curriculum, you will have the opportunity to attend courses about mobility modelling, spatial mobility, economic geography, simulation, deep learning, and artificial intelligence. You will gain hands-on experience with state-of-the-art techniques applied in ICT through themes related to mobile data, cellular networks, intelligent transport systems, and autonomous driving.
Matching career profiles
The University of Tartu is a great choice for those seeking professional placement in government agencies or private companies as a data scientist with profound expertise in transportation and mobility.
Specific entry year requirements
Due to a strong technological focus, applicants are required to have completed at least 24 ECTS worth of courses in computer science such as programming, algorithms or data structures. Additionally, essential knowledge of geographic information systems as well as basic programming constructs is strongly recommended.
Specific exit year requirements
- Ability to design, implement, test, and debug algorithms for solving basic text-based problems.
- Understanding of basic data types and structures (e.g., numeric types, booleans, strings, lists) and the corresponding operations.
- Knowledge of probabilistic computations, random variables, distributions, and the ability to apply these in typical scenarios.
- Competence in mathematical statistics, including point and interval estimation, hypothesis testing, and critical evaluation of data in public media.
Why Tartu?
Tartu, Estonia’s oldest city, blends rich history with modern vibrancy. As the cradle of Estonian culture, it features medieval ruins, lively cultural events, and charming cafés. With students making up a quarter of its population, Tartu buzzes with youthful energy, offering a unique mix of tradition and innovation in a city full of charm and discovery.
Polytechnic University of Catalonia
The SMDSA track at Polytechnic University of Catalonia is designed to meet the specialised skills and knowledge needed to navigate the evolving urban transportation landscape, providing students with a comprehensive understanding of the role of data in shaping urban mobility.
Contents at a glance
The curriculum allows students to engage with cutting-edge research and industry practices through lectures, workshops, and fieldwork. Mandatory courses aim to provide fundamental knowledge on transportation engineering and urban planning, providing the students with the necessary tools to analyse and design innovative solutions for urban mobility. Courses address transportation operations & management, data analysis & optimisation, travel demand & behavioural modelling, city planning, and decision-making & economy in urban mobility. Later on, students take specialised courses such as Machine Learning or Data Analysis and Knowledge Discovery, which delve into data science applied to the design of innovative solutions for urban mobility.
Matching career profiles
The Polytechnic University of Catalonia is a great choice for careers in various professional areas, including urban planning, passenger mobility, freight logistics, transportation consulting, transport analytics, and policy development.
Specific entry year requirements
Due to a strong focus on engineering, it is strongly recommended for applicants to have an engineering degree (including Industrial, Civil, Construction, Telecommunications, Informatics, Engineering Physics, and other fields of engineering). Additionally, elementary knowledge of probability and statistics, linear algebra and real analysis, as well as good programming skills in a high-level language are necessary.
Specific exit year requirements
- Basic competences in algorithms, data structures, and databases.
- Basic knowledge of Computer Science principles, including: Notions of computer architecture, Basic programming constructs, Data structures.
- Good command of several programming languages.
- Basic ability to formalise issues mathematically in informatics engineering.
- Sufficient knowledge of data analysis methods, including: Probability functions and analysis of variance (ANOVA) models.
- Recommended knowledge about transportation modeling, transport demand and traffic flow theory.
Why Barcelona?
Barcelona provides a vibrant setting for studying sustainable urban mobility, combining a rich urban history with innovative smart city initiatives. From the historic Cerdà Plan to modern “Superblocks” and extensive bike lanes, the city showcases diverse mobility solutions. Students benefit from site visits, guest lectures, and internships, gaining firsthand experience and insights into future urban mobility while joining a forward-thinking community shaping tomorrow’s cities.
Ghent University
The SMDSA track at Ghent University aims to improve urban mobility in cities worldwide through a systems approach, teaching students how to analyse complex flows and relationships in urban environments and support decision-making based on urban data.
Contents at a glance
The curriculum trains students in designing and managing mobility and logistics operations of cities and large companies, based on data-driven and expert-based decision-making processes. Transport engineering is taught through key learnings in traffic modelling, simulation and operations research with an additional focus on artificial intelligence. The courses teach you how to build AI decision models for planning and scheduling urban services and critically understand their impact to help cities’ decisions on the most pressing challenges. Team projects include urban challenges defined by governmental and industrial stakeholders, and learning how to pitch the value to decision-makers and citizens.
Matching career profiles
The Ghent University is a great choice for those seeking to work for government agencies or consultancy/engineering/IT companies in integrated planning, passenger mobility, freight logistics or urban services.
Specific entry year requirements
Applicants are required to be familiar with basic programming skills, linear algebra, discrete mathematics, stochastic simulation and related concepts. Additionally, the programme is made for students who possess an entrepreneurial attitude with self-steering capacity, perseverance, flexibility, and creativity.
Specific exit year requirements
- Introduction to Operations Research
- Basic programming skills, including experience with Python.
- Understanding of basic data analysis methods and probability.
- Insight into the building blocks of business models, including development and evaluation.
- Capability to validate and work on business ideas, either personal or from fellow students.
- Basics of transportation modelling and traffic flow.
Why Ghent?
Ghent, the largest student city in Flanders with 48,000 students, blends a cosy atmosphere with an international community. A leader in urban mobility, it features extensive pedestrian zones, a citywide Low Emission Zone, and progressive cycling policies. Known for its vibrant culture and sustainability, Ghent fosters creativity, entrepreneurship, and diverse lifestyles in a dynamic and innovative environment.
University of Lisbon-Técnico.IST
The SMDSA track at the University of Lisbon Técnico.IST provides strong knowledge in transport and its relation to urban planning, along with skills to tackle urban mobility challenges.
Contents at a glance
The curriculum combines technical expertise with strategic and analytical skills to address complex transport challenges. Core courses focus on sustainability, transport technologies, policy, and urban planning, while optional subjects like big data analytics, geographic modeling, and entrepreneurship enable specialisation. Practical application is emphasized through challenge projects aimed at developing innovative solutions in transport systems.
Matching career profiles
The University of Lisbon is a great choice for careers focused on technological innovation, data analysis and modeling within the fields of urban and transport planning.
Specific exit year requirements
Applicants are required to have completed at least 24 ECTS worth of courses in mathematics, physics, statistics and/or computer science. Additionally, they should be familiar with the basics of probability and statistics, as well as system thinking principles.
Specific entry year requirements
- Basic knowledge of microeconomics
Why Lisbon?
Lisbon, a dynamic hub for master’s students, combines rich history with forward-thinking urban mobility innovations. Known for its iconic trams and walkable streets, Lisbon has embraced modern sustainability with projects like extensive bike lanes, electric mobility initiatives, and an efficient public transport network. Its dynamic culture, warm climate, and entrepreneurial spirit create an inspiring environment for students pursuing academic and professional growth in a city shaping the future of mobility.
*NB: If you choose Ghent University as one of your preferences, you need to submit a separate application on Ghent University’s Online Application Platform, in parallel with your EIT Urban Mobility Application. Please check our detailed information page‘s Application dates and deadlines.
When selecting your Entry and Exit University, careful planning is vital. We urge all applicants to thoroughly study the course lists offered by each partner university. By carefully examining the courses available, you can ensure alignment with your academic skills and interests, career aspirations, and personal goals. Your choice lays the foundation for your academic success and influences your learning experience in the programme. Whilst your application is evaluated in line with your university preferences, some applicants may be assigned to alternative universities that better fit the profile of the application.
Programme Lead
Dr. Amnir Hadachi
Institute of Computer Science, University of Tartu
Dr. Amnir Hadachi is Head of the Intelligent Transportation Systems Lab and a lecturer at the Institute of Computer Science of University of Tartu. He is also an active member of EIT Urban Mobility and Associate Editor of Elsevier Journal of Urban Mobility. He has been leading, and involved in, many projects for applied research funded by the European Regional Funds, Inter-Ministry Fund, EIT Urban Mobility, and several IT companies. Additionally, he has been keen on developing and strengthening collaborations between academia and industry in Estonia and at the University of Tartu, which has led him to receive the award “Applied Researcher of the Year” for his applied research activities and collaboration with industry in 2019 by the Institute of Computer Science. He received his PhD in Computer Science from the National Institute of Applied Sciences (INSA de Rouen), France, in 2013. His main field of research is related to spatio-temporal data analytics and mobility modelling, focusing on intelligent transportation systems, location-based services, smart cities and autonomous vehicles.
