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Frankfurt am Main, 30.01.2018 12:00:00

Since the start of the recent academic year Frankfurt School of Finance & Management has incorporated the new core module Data Analytics and Machine Learning in the Master of Finance to prepare students for a career in a disruptive working environment. The course aims to enable participants to handle, analyse and interpret big data especially in financial contexts.

Professor Dr Grigory Vilkov, Academic Director of the Master of Finance and Professor of Finance at Frankfurt School, is convinced that skills such as coding are important for the path to success in any career. “We want to ensure that our students are well prepared to start working in demanding positions when they graduate. Hence, nowadays young professionals need a technical skillset. Therefore, we offer state of the are academic programmes and teach our students to analyse data so they can make fast and qualified decisions,” says Professor Vilkov. According to the expert programming is a tool to access and organise large amounts of data.

Professor Dr Grigory Vilkov

Professor Dr Grigory Vilkov

“Summing up, the most significant skills our students learn in courses such as Data Analytics, Machine Learning and Algo Trading & Financial Analysis are coding, data retrieval and organisation as well as efficient data handling for a number of purposes and various applications,” emphasises Grigory Vilkov.

Alexander Maas who started the Master of Finance at Frankfurt School in 2016, stresses how he has learned to source various forms of financial data for analyses:

“In the course Algo Trading & Financial Analysis I learned about the common programming syntax for Python, the different packages in Python and the uses for each.” In his view, it is essential to learn a lot about Data Science due to the demand of companies asking for knowledge in programming.

A student in the Frankfurt School Finance Lab

A student in the Frankfurt School Finance Lab

Ion Tapordei, Master of Finance student Class of 2018, thinks that the amount of data available and continuously generated in the financial environment gives the opportunity of making better financial decisions. Therefore, the ability to analyse data is essential.

“Today the challenge in finance is the ability to analyse a lot of data in an efficient manner, to derive relevant models and eventually to automatise the process in an algorithm. This is a toolset that can make an essential difference for a successful finance professional,” explains Ion Tapordei. In this context, Ion Tapordei underlines the path of Frankfurt School to involve more and more subjects in Python. “Frankfurt School continues doing what it stands for – preparing future talents for the industry,” he adds.

Meanwhile, in order to broaden the technical skills of all students, the Frankfurt School curriculum includes learning programming languages such as Python in nearly all academic programmes. This is for both undergraduate education as well as in postgraduate education.        

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