Web and Data Science (MSc)

Overview

This English-language Master of Science builds specialised skills for analysing data and for designing and developing web- and data-intensive systems. The programme treats the web and data ecosystems as multi-dimensional environments shaped not only by technology but also by economic forces and social interactions among individuals, organisations, companies and governments. Students learn to work with both the technical and socio-economic aspects that influence how data and web systems are created, used and governed.

Curriculum focus and outcomes

The course aims to give a solid, research-oriented foundation in the techno-sociological nature of web and data-intensive systems. You will deepen your abilities in designing and implementing web systems, perform automated analysis of data (including web content, link structures and usage data), and consider legal, social, economic and political influences — for example digital rights, social network dynamics, online consumer behaviour and e‑participation. The programme emphasises problem formulation, teamwork, independent academic work and transferable skills so graduates can analyse data, craft data-driven narratives, build interactive web presences and develop web- or data-driven strategies for organisations. It also prepares students for further academic development, including doctoral studies.

What the programme expects graduates to achieve

• Fully internalise and extend the concepts and competencies acquired during a relevant Bachelor's programme, showing greater maturity and confidence in applying them to new domains
• Possess deep knowledge of data analysis and visualisation, web system development, web strategies and the broader web/data ecosystem
• Have the breadth and depth to learn and adapt to future technologies in their field and adjacent areas
• Be able to apply Data Science and Web Science methods to define and solve complex research and development problems in the public sector, ICT industry and research institutions
• Critically evaluate existing knowledge and, where needed, contribute to its further development
• Demonstrate technical and social skills such as abstraction, systems thinking, communication, teamwork and international/intercultural competence — preparing them for leadership or managerial roles
• Be acquainted with academic research practices and meet the prerequisites to pursue a doctorate if desired

This Master’s curriculum is designed to give you a high degree of flexibility and research involvement, helping you develop into an independent academic and practitioner. The program is interdisciplinary, centring on computer science and data science while deliberately connecting to social sciences, economics, law, linguistics and mathematics. All courses are delivered in English, and the course structure encourages students to shape their study paths around personal interests and research goals.

Core teaching is organised into five module groups that balance theoretical foundations, practical methods and transferable skills. Web Science modules introduce web engineering, social network models and broader conceptual views of web structures. Data Science modules cover big data and machine learning fundamentals, including data acquisition, analysis and communicating results so they can be turned into actionable insights and strategic plans. A substantial elective component lets you tailor your profile with mathematical modelling, information management, business informatics, computer science or other research-led subjects. Research seminars, lab work and a dedicated social-skills/leadership training component prepare you for collaborative projects and professional roles. The master’s thesis is an independent research project on any topic within web and data science.

Key modules and outcomes (concise)

• Web Science (3 modules): web science foundations, web engineering principles, and social networking models — learn to analyse and conceptualise web and abstract web structures.
• Data Science (3 modules): core big data and machine learning concepts — gain skills in sourcing, analysing, visualising and communicating data; convert analyses into practical, strategic insights.
• Mandatory elective courses (36 ECTS): choose from subgroups in Mathematical Modelling, Information Management, Business Informatics, Computer Science and other research-based subjects to deepen technical, mathematical or management competencies.
• Seminars and Research Lab: topics freely chosen from web and data science areas; hands-on research experience and presentation of results.
• Social skills and leadership training (part of seminar/lab group, 16 ECTS): develop teamwork, leadership and professional communication abilities.
• Master’s Thesis (30 ECTS): an independently chosen research project within web and data science demonstrating subject mastery and research maturity.

Graduates are equipped to work in research and development roles across the public sector, ICT industry and research institutions, where they can apply data science and web science methods to complex problems. Typical responsibilities include designing data-driven products and services, performing advanced data analyses and visualisations, developing web presences and devising web or data strategies for organisations.

The degree also prepares students for leadership or managerial roles by developing technical expertise alongside social and communication skills, and it fulfils the academic prerequisites for continuing to doctoral studies.