The programme at a glance – 120 ECTS
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Duration:2 years / 4 sem
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Teaching languages:EN
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Admissions:EU: 1 Feb 2025 – 27 Aug 2025
Non-EU: 1 Feb 2025 – 30 Apr 2025
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Fees:400€/ sem. (semester 1,2,3,4)
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Format:Full-time programme (Part-time student status allowed)
Dates coming soon
Presentation
MADS provides high-level multidisciplinary training conducted by renowned research teams from Luxembourg and abroad. The course relies on theoretical and practical aspects, and also involves projects and workshops. MADS can be taken either as a two-year four-semester programme, or as a four-year part-time programme. The courses are given in person and presence in class is compulsory. Part-time students share the same courses during the day as full-time students (no week-end and late courses are offered).
How to find an answer to your questions?
- Some eligibility criteria (diploma recognition, language certificates, etc.). You will find more information by clicking HERE
- For specific administrative questions, please contact SEVE by clicking HERE.
- Admission criteria for the MADS programme are described on the following webpage INFO
- For recognition of prior experience, please click HERE
- Information about student life and cost of living. You can find more information by clicking HERE
More info
Scholarship
A scholarship is currently offered for this Master programme: the Guillaume Dupaix International Scholarship. For more information, please send your request to: scholarships.fstm@uni.lu
Strengths
- Addressing fundamental and practical aspects of Data Science
The programme trains students in modern data management and processing techniques. It also provides the mathematical foundations upon which these techniques are built. As a result, students acquire not only a high-level education in current data science techniques but also sufficient scientific knowledge to adapt and further their training for future advancements in this field. Finally, the programme offers students a diverse overview of the applications of data science, spanning the fields of life sciences, actuarial sciences, and economics among others.
- Variety of skills
The graduates acquire a broad spectrum of skills with cross-disciplinary applications: data mining, data cleaning and processing, data visualisation, statistical modelling, database management, workflow organisation, machine and deep learning.
News
Contact
For any question regarding the Master in Data Science, please send your request to