Data Science (MSc)

Program overview

This English-taught Master’s program in Data Science builds on a solid Bachelor’s background and is aimed at students who want to deepen their expertise and work with cutting-edge technologies. The curriculum is positioned at the crossroads of scientific research and industrial application, preparing you to contribute to both academic and practical solutions.

What you will learn

You will be trained in AI-supported decision-making that leverages existing mathematical models to tackle important societal challenges. The program places special emphasis on quantifying uncertainty and on causal and Bayesian inference methods. You will also study modern approaches in reinforcement learning and data assimilation—techniques that are actively used to improve predictions and decisions in areas such as climate change, weather forecasting, and medical research. In addition, the course familiarises you with essential IT tools for contemporary data work, including cloud computing and data management.

Why this matters

The combination of probabilistic reasoning, model-based decision support, and scalable IT skills equips you to work on high-impact problems where reliable predictions and sound uncertainty handling are critical. The program is well suited for students aiming for roles in research, industry, or interdisciplinary projects that address pressing societal issues.

Entry profile (concise)

• Completed Bachelor’s degree in a relevant field (solid quantitative background expected)
• Proficiency in English (program language: English)
• Strong interest in AI, uncertainty quantification, Bayesian/causal inference, reinforcement learning, and data assimilation
• Familiarity or willingness to work with programming, cloud computing, and data management tools

Curriculum overview

This MSc curriculum is structured to balance advanced coursework, hands-on projects and an independent research thesis. Nearly one third of the program (29%) is devoted to compulsory advanced data science topics, ensuring a strong, coherent core. Elective study for specialization accounts for 21%, allowing you to tailor the degree to particular interests. Another 21% is allocated to individual projects that give practical, applied experience. Soft skills and language training make up 4%, and the remaining 25% is reserved for the master's thesis, the programme’s culminating research or development project.

Key modules and learning outcomes are aligned with these components. The compulsory advanced-topic modules deepen theoretical and methodological understanding of data science; elective modules let you develop domain-specific depth; individual projects provide supervised, practical application of methods; soft skills and language sessions build professional communication and intercultural competence; and the master's thesis develops independent research, problem formulation, and technical reporting abilities.

Graduates will emerge with a combination of high-level conceptual knowledge, applied project experience, and the capacity to carry out substantial independent work—preparing them for careers in industry, data-driven roles, or further research.

Curriculum breakdown (requirements)

• Compulsory advanced data science (advanced topics): 29%
• Elective area (specialisation): 21%
• Individual projects: 21%
• Soft skills and languages: 4%
• Master's thesis: 25%

Graduates will be prepared for roles that require advanced quantitative and algorithmic expertise, such as data scientist, machine learning engineer, research scientist or specialist in data assimilation and model-based decision support. The programme’s emphasis on uncertainty quantification, causal/Bayesian inference and reinforcement learning equips alumni to work on high-stakes applications in climate science, weather forecasting, healthcare and other sectors where reliable predictive models and principled decision-making are essential.

The combination of theoretical foundations and practical IT skills (cloud computing, data management) also supports transitions into industry positions in tech, analytics, consulting and R&D departments, as well as further academic research (PhD) pathways. The optional double-degree with LUT University can additionally enhance international mobility and career prospects in Europe and beyond.