Descrizione della formazione

Data?science combines mathematics, statistics, computer science, and engineering to extract knowledge from data, support evidence based decision making, and build adaptive systems that learn from experience. Over the past decade it has become indispensable in domains as diverse as pharmaceutical research and development, medical imaging, computational social science, digital humanities, and public policy.

Today’s wave of «generative AI»—especially large language models and diffusion models—has amplified that impact: LLM (=Large Language Model) powered assistants summarise medical literature in seconds, protein folding networks accelerate drug discovery, and foundation model surrogates speed up climate simulations. These advances illustrate the «unreasonable effectiveness» of data driven methods and are reshaping legal frameworks, public debate, and the very ways we work, think, and communicate.

A typical data science workflow starts with exploratory analysis and data cleaning, progresses through modelling and scalable computation, and culminates in clear visualisation and communication of new knowledge. Because of its sweeping importance, data science is often called the «fourth pillar» of scientific inquiry, standing alongside theory, experiment, and computational science.

Focal area of teaching and research

The MSc in Data Science at the University of Basel offers a rigorous foundation in mathematics, statistics, and machine learning together with a full repertoire of modern systems courses for secure, efficient handling of large scale data. 

Key features 

• Integrated AI & LLM track – new modules on AI, generative modelling, and foundation models complement the existing machine learning core.
• AI?for?Science electives – choose from courses ranging from computational biology to psychology that demonstrate how data science drives discovery.
• Scalable systems training – hands on work with distributed databases, clusters, and GPU accelerators housed in sciCORE—University of Basel’s high-performance computing facility.
• Research immersion – through the University’s Center for Data Analytics you can write your Master’s thesis on real world data drawn from life sciences, fintech, humanities, or physics, supervised by internationally recognised faculty.

 The two year, 120?ECTS programme culminates in the degree Master?of?Science in?Data?Science, and provides an ideal springboard to PhD study in Data Science, Computer Science, or Mathematics, or to leadership roles in academia.

Course structure Master studies

The Master of Science degree is the postgraduate degree after the Bachelor's programme. The program awards 120 ECTS credits in total. The Specialized Master’s degree program Data Science is a so called «mono-course» consisting of only one core subject.

Piano di formazione

One ECTS credit point roughly equals 30 hours of study. 

Combinazione di indirizzi

The degree programs at the Faculty of Science are generally mono-courses with the possible addition of an in-depth subject and an elective subject.