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.
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.
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:
Learn how to practically analyse large-scale business data using machine learning techniques.
Learn basics of analysing data in R
Apply what they have learned to real finance data
Learn how to use statistical methods for strategic decision making.
Regression and classification
Supervised and unsupervised learning
Data analysis in R
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
Course materials will be provided in electronic form.
Partially online via Zoom and Campus Westend of Goethe University Frankfurt.
A GBS certificate of participation is awarded upon completion of the course.
€ 1.900 (fee is exempt from VAT). The fee for GBS students or alumni amounts to € 800.
*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.
|Offered in SS 2022|