Executive Education


Big data is one of the buzzwords in today’s business world. Since computers became more and more central to modern commerce, businesses have access to large amounts of data, for example, on their customers or transactions. This gives companies the opportunity to extract useful information using statistical and machine learning methods in order to gain a competitive advantage. The big internet companies are the obvious examples, but the topic is also especially relevant for the financial industry (like with credit analysis, fraud detection, insurance and robo-advising). In many areas these new technologies will disrupt existing business models.

The course will focus on the analysis of Big Data, and how it can be used for prediction, for example bankruptcies or stock prices. Even though the course will focus on supervised learning techniques such as regression and classification, we will also touch upon unsupervised learning techniques.


Ludmila Ketterer

 +49 69 798 33512



This course is offered in the part-time Master in Finance program and may be attended on a “no credit” basis by individuals not enrolled in the program. Course participants are visitors who are not responsible for assignments and do not take an exam or earn academic credits. As the number of seats in the course is limited, we recommend to register online early.


Upon completion of this course, you will be able to:

practically analyse large-scale business data using machine learning techniques

apply basics of analysing data in R

apply learnings to real financial data

use statistical methods for strategic decision making


   Machine learning
   Regression and classification
   Supervised and unsupervised learning
   Data analysis in R


Prof. Dr. Uwe Walz

Uwe Walz holds the Chair of Industrial Organization at Goethe University, and is co-Director of the PhD Program in Economics. Uwe Walz received his Ph.D. in economics from the University of Tübingen in 1991 and completed his habilitation at the University of Mannheim in 1995. Prior to joining the faculty of Goethe University in October 2002 he was a Professor of Economics at the University of Bochum (1995-1997) and at the University of Tübingen (1997-2002). Furthermore, he was a visiting research fellow at the London School of Economics and at the University of California at Berkeley. Prof. Walz is Director of the research program “Entrepreneurial Finance” at the Center for Financial Studies (CFS) and research professor at the center for European Economic Research (ZEW). His main current research focuses on private equity, entrepreneurial finance and contract theory as well as on the economics of network industries. Prof. Walz has published widely in international journals, most recently on venture capital topics and organizational design. His work has appeared in journals such as the Journal of Corporate Finance, the Journal of Financial Intermediation, the Journal of International Economics, the European Economic Review, and the Journal of Public Economics.


Assoc. Prof. Dr. Steffen Juranek

Steffen Juranek is an Associate Professor at Norwegian School of Economics since 2017. He received his Ph.D. from Goethe University Frankfurt in 2012. His research focuses on the organization of firms and markets, and the role of intellectual property for firm strategy, financing and taxation. Prof. Dr. Juranek taught courses on statistics, management control, R&D and intellectual property. His research has been published in international journals


Key Facts

Course materials

Course materials will be provided in electronic form.




Partially online via Zoom and Campus Westend of Goethe University Frankfurt.

Certificate of participation

A GBS certificate of participation is awarded upon completion of the course.

Course Fee*

€ 950 (fee is exempt from VAT). The fee for GBS students or alumni amounts to € 400.

*Withdrawal and fee refund
In case the course withdrawal request is received two weeks prior to the start of classes, GBS will retain a withdrawal fee of €50. In case the course withdrawal request is received less than two weeks prior to the start of classes, GBS will retain 50% of the payment made.

Course Schedule
Date Session
Sat., June 5, 2021 18:00 - 20:00
Fri., June 18, 2021 18:00-20:00
Sat., June 19, 2021 14:30-16:30
Sat., July 3, 2021 09:00-11:00
Sat., July 17, 2021 09:00-11:00 11:30-13:30

There are two main things which make returning for Open Programs such a valuable and worthwhile experience. The first is being back on campus – meeting the current students, returning to campus again, the whole experience was just so pleasant. The second is the level of quality in the courses – the faculty teaching are absolute experts.

Stephan KieneDuke-Goethe Executive MBA Class of 2009


Already convinced?
Register for our Big Data in Finance program now.


Bulletin Open Programs

Sign up to be informed about latest Open Enrollment programs.