Data Science Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Overview

Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) is renowned for its strong emphasis on interdisciplinary collaboration, particularly between the departments of mathematics and computer science. This unique synergy enhances the learning experience, allowing students to engage with a broad spectrum of topics in both fields. The university is strategically located in the Nuremberg metropolitan area, which boasts a thriving industrial environment that fosters practical applications of academic knowledge. This proximity to leading companies such as Siemens, Schaeffler, and adidas provides students with opportunities to network and potentially secure employment during their studies.

The tuition fees for the Data Science programme are as follows:

• International Fee: EUR 0 per year
• European Fee: EUR 0 per year

Visit the Fees and Funding section for a breakdown in your local currency.

The M.Sc. in Data Science programme encompasses a range of specialisation areas and core modules, structured to provide both depth and breadth in the field. Students must select one major field of study, completing modules totalling 30 ECTS, while also engaging in minor fields with 20 ECTS. The core modules, amounting to 15 ECTS, are mandatory for all participants. The specialisations include:

• Data-based optimisation
• Mathematical theory / Fundamentals of data science
• Databases and knowledge representation
• Machine learning / Artificial intelligence
• Simulation and numerics
• Mathematical statistical data analysis

Additionally, students will complete technical qualification modules (5 ECTS) and choose application subjects from a diverse array, such as:

• Artificial intelligence in biomedical imaging
• Digital humanities
• Medical data science
• Geosciences
• Physics

The programme culminates in a Master’s seminar (5 ECTS) and a Master’s thesis (30 ECTS) in Data Science.

Graduates of the M.Sc. in Data Science are well-prepared for a variety of career paths due to the high demand for data science professionals. Potential employers span multiple industries, including:

• Technology sector (e.g., Google, Microsoft, IBM)
• Consulting firms (e.g., McKinsey, Deloitte)
• Biomedical research (e.g., AstraZeneca, Roche)
• Logistics (e.g., Deutsche Post, UPS)
• Energy sector (e.g., E.ON, RWE)
• Finance and insurance (e.g., Deutsche Bank, Allianz)

With a significant shortage of data science experts in Germany, graduates can anticipate competitive starting salaries. Those wishing to further their academic pursuits may also consider continuing to a doctoral programme, contributing to the evolving landscape of data research and its applications.