31 July 2021
Data Science for Financial Problemsonline course
Application of Data Science, Computational Intelligence and Machine learning in the domain of Finance and Financial Services Technologies is a hot topic. There is a huge spectrum of various technologies that are available in libraries in the form of open-source or open-access form that can be used effectively in the domain of Finance. Now, one of the important issues is how to support SME (Small and Medium-Sized Enterprises), micro firms and start-up in symbiosis with a financial institution that have available data of enterprises as e.g., bank account, electronic invoices, taxing data through supporting to transmit the tax information to Tax Authorities in a timely fashion. The financial institution and their subsidiaries can access data that are not open for everyone. Thereby, the methods that were traditionally called Business Intelligence and Business Analytics with the extension of the most recent Data Science can yield a value-added set of services exploiting the rich palette of data analytics like deep learning, TensorFlow, complex time series, natural language processing, etc.
During the summer school, participants will get acquainted with a framework of state-of-the-art technology that will support visual programming and allow alternative approaches of algorithms, comparing the results on the various data sets using the standard metrics. The theoretical background e.g., time series analysis and “business intelligence”, can be studied and employed on business and financial cases. It will cover foundational concepts and practical knowledge in hands-on sessions.
Since the primary focus of the program is on the expertise in innovation and entrepreneurship, participants will work on business assignments for the innovative use of machine learning in cooperation with companies and start-ups from the Budapest ecosystem.
We welcome all qualified participants interested in digital innovation and entrepreneurship: Business professionals, bachelor’s degree students, master’s degree students, and doctoral students from any university and industry.
Acceptance of transfer credit is always a decision of receiving institutions. Any student interested in transferring 4 ECTS credits to another college or university should check directly with the receiving institution.
EUR 1650: Regular rate.
EUR 1250: Special tuition fees for organisations that register 5 or more participants. Please contact EIT Digital Summer School for invoicing details.
Stipends and grants details available on the website.