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Trailer zum Programm
DVFA Webinar: A View into the Future - Financial Data Science


Ulf Mayer, CIIA, CEFA

+49 69 26 48 48 - 124


Start: April 27, 2017

Detailed schedule can be found on the registration form.

CFDS - Certificate in Financial Data Science

  • 6 days in-class + approx. 70 hours of online self study + project work
  • Includes practical Python training session
  • Exam includes Financial Data Science Project

This program aims to introduce finance professionals into the potentially endless opportunities which arise when insights scientifically extracted from big data are empowering financial market participants.

Successful participants will significantly enhance their abilities and employability in six ways:

  1. understand the implications of the gradual shift from the assumption based decision making of the 20th century to the evidence based, data driven decision making of the 21st century.
  2. learn to critically assess the information value of a variety of different data sets based on data source and scientific characteristics.
  3. learn to understand asset management as a data–analysis–decision–data process including general knowledge of the most effective statistical procedures for explaining the variation of asset prices.
  4. enjoy a practical session of training in the currently most popular programming language of Financial Data Science: Python.
  5. will be introduced into the world of Big Data, machine learning and deep learning methods to source insights from these data riches.
  6. learn how to visualise and communicate valuable insights gained through Financial Data Science.

CFDS – Certificate in Financial Data Science started

First class of the CFDS – Certificate in Financial Data Science started with 8 participants, mainly from major asset management companies.

cfds 1. jg


a) Introduction into Financial Data Science

b) Exploring and Analysing Data

c) Data & Asset Management: does the asset create data or is independent data the asset?

d) The Science of Data

e) Understanding Asset Management from a financial data science perspective

f) Statistical Analysis of asset price variation

g) Python for Financial Data Science

h) Big Data Storage and Retrieval

i) Machine Learning

j) Deep Learning

k) Data Visualization and Communication of Outcomes

Course Scope & Assessment

  • Course will be offered throughout Europe, hence taught in English
  • Total of 24 "days" of study and project work including

    • 3 in-person workshops of 2 days each
    • approx. 9 days of self study with online material
    • project work

  • Passing the exam after the first two workshops is a prerequisite to qualify for the project work.
  • Students will be assessed based on a Financial Data Science project which they will present to the course lecturers and their peers in a final workshop.

Scientific Directors & Lecturers

Dr Damian Borth
Director of Deep Learning Competence Center & Head of Multimedia Analysis & Data Mining at German Research Center for Artificial Intelligence (DFKI)

Dr Damian Borth is the Director of the Deep Learning Competence Center at the German Research Center for Artificial Intelligence (DFKI), the Principle Investigator of the NVIDIA AI Lab at the DFKI. Damian’s research focuses on financial data science, machine learning, and deep learning. His work has been awarded by NVIDIA at GTC Europe 2016, the Best Paper Award at ACM ICMR 2012, the McKinsey Business Technology Award 2011, and a Google Research Award in 2010. He is also a founding member of the Financial Data Science Association. Damian did his postdoctoral research at UC Berkeley and the International Computer Science Institute (ICSI) in Berkeley where he was also involved in big data projects at the Lawrence Livermore National Laboratory. He received his PhD from the University of Kaiserslautern and the German Research Center for Artificial Intelligence (DFKI). He was also a visiting researcher at the Digital Video and Multimedia Lab at Columbia University in 2012.

Dr Andreas Hoepner
Associate Professor of Finance at the ICMA Centre of Henley Business School

He is currently also heading the ‘Practical Tools’ research group of the Mistra Financial Systems (MFS) research consortium. Dr Hoepner serves as the inaugural chair of the Financial Data Science Association and sits on independent assessment committees for the Investment & Pensions Europe (IPE) Awards, the Investment Innovation Benchmark (IIB), and the RI Awards. He sits on advisory boards for Bank J. Safra Sarasin, the Carbon Disclosure Project (CDP) and French Social Investment Forum (FIR).
Andreas received his PhD from St Andrews in June 2010, where he was on faculty 2009 to 2013 and built up the Centre for Responsible Banking and Finance as its Deputy Director. He is founding co-director of a social enterprise (Sociovestix Labs, a spin-off from the German Research Centre for Artificial Intelligence [DFKI]).
Dr Hoepner’s financial data science research has made him sole inventor of the US patent investment performance measurement (No. US8751357 B1)

Online Study Material

The study material will consist of a set of crucial articles to study basic structure of financial data science and recommended video clips describing the weaknesses of classic financial economics. Hereby, the material will focus on (i) why financial data science offers a wealth of opportunities unavailable in financial economics, (ii) what structural changes are to be expected as a result of such opportunities especially in the context of regulatory initiatives such as MiFID, (iii) how participants can train themselves in financial data science techniques and thinking and (iv) who students might want to team up with to realise the full potential of financial data science.

Web-Ressources on Financial Data Science


The in-class workshops and the exam will take place at DVFA Center, located in central Frankfurt close to the main station and in good reach from the airport

DVFA Center
Mainzer Landstraße 37-39 (François-Mitterrand-Platz)
60329 Frankfurt am Main

Location Map DVFA Center


For registration to the CFDS programme please complete the regisration form and return by fax or mail to DVFA.



€ 8.450 zzgl. MwSt.

Early bird

€ 7.950 zzgl. MwSt.

Super early bird € 6.950 zzgl. MwSt.


Discount for multiple booking on request.

Participation fee includes 3 workshops, online resource, exam and project work assesment. Participants need internet access, to watch videos a certain bandwidth might be necessary.

For German participants:

Aufwendungen für die Fortbildung in dem bereits erlernten Beruf sind grundsätzlich als Werbungskosten bzw. Betriebsausgaben in voller Höhe abziehbar. Mehr Informationen dazu finden Sie auf der Seite der IHK Frankfurt.

Credit Points für DVFA Mitglieder

Nach erfolgreichem Abschluss des CFDS-Programms erhalten DVFA Mitglieder 10 Credit Points im Rahmen ihrer Selbstauskunft. Weitere Informationen zur Mitgliedschaft finden Sie hier.