Chartered Financial Data Scientist (CFDS®) | English Qualification program

Normaler Preis €0,00 €10.341,10     inkl. MwSt. Angebot

KURSBESCHREIBUNG

Course Description

CFDS® – Chartered Financial Data Scientist

”Data Scientist: The Sexiest Job of the 21st Century.”

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.

Chartered Financial Data Science - CFDS®

Press

KI-Systeme sind Digitale Fachidioten. Dr. Damian Borth, Deutsche Forschungsstelle Künstliche Intelligenz, im Interview mit dem Handelsblatt am 27. Juli 2018

Neues Berufsbild Financial Data Scientist. Ein intelligentes Zusammenspiel von Mensch und Maschine. Von Ralf Frank, DVFA, Prof. Dr. Andreas Hoepner, University College Dublin, Dr. Damian Borth, Deutsche Forschungsstelle Künstliche Intelligenz. Börsen-Zeitung, Sonderbeilage Digitalisierung, 8. März 2018

Financial Data Scientist – a new investment profession. By Ralf Frank, DVFA, Prof. Dr. Andreas Hoepner, University College Dublin, Dr. Damian Borth, German Research Center for Artificial Intelligence.

Er ist Deutschlands "Mister Deep Learning". Portrait Dr. Damian Borth. Frankfurter Allgemeine Zeitung, 3. Juli 2017

 

Learning Goals

Successful participants will significantly enhance their abilities and career prospects in 6 distinct ways:

  • 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.
  • Learn to critically assess the information value of a variety of different data sets based on the data source and scientific characteristics.
  • Learn to understand asset management as a data–analysis–decision–data process, including general knowledge of the most useful statistical procedures for explaining the variation of asset prices.
  • Enjoy a practical session of training in the currently most popular programming language of Financial Data Science: Python.
  • Will be introduced into the world of Big Data, machine learning, and deep learning methods to source insights from these data riches.
  • Learn how to visualize and communicate valuable insights gained through Financial Data Science.

    Online Study Material

    The study material will consist of a set of crucial articles to study the 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) which students might want to team up with to realize the full potential of financial data science.

    Target Groups

    • Data Analytics

    • Data Management

    • Risk Management

    • Marketing/Sales

    • Trading

    • Compliance/Regulation

    • IT

    Personal Requirements

    Programming skills are not required but some prior knowledge in statistics, e.g. in probability distribution, will be of help.

     

    Syllabus

    a) Introduction to 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

    Exams

    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.

     

    Registration Fees

    Regular  € 8.690 plus VAT.  

    Early bird  € 8.190 plus VAT

    Super early bird  € 7.190 plus VAT

    Discount for multiple bookings on request, please send an email.

    Information for Participants

    Participation fee includes 3 workshops, online resource, accompanying webinars, exam and project work assessment.

    Participants need internet access, to watch videos a specific 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.

    Dates

    • tbd

    • English
    • Total of 24 "days" of study and project work
    • 3 in-person workshops of 2 days each; accompanying webinars
    • Approx. 9 days of self-study with online material (avg. of 5 hours per week)
    • Lecturers: Prof. Dr. Andreas Hoepner and Prof. Dr. Damian Borth
    • Downloads: 
    • CFDS® brochure (PDF) 
    • Registration form (PDF)

    YOUR CONTACT

    Stefan Schummer, Program Manager

    Tel.: +49 69 26 48 48 - 121

    Send email

    Über den Referenten

    Prof. Hoepner, CFDS, DVFA

    Prof. Hoepner, CFDS, DVFA

    Vita:

    Professor of Operational Risk, Banking & Finance at University College Dublin

    Visiting Professor of Financial Data Science, University of Hamburg

    Visiting Professor of Finance, ICMA Centre, Henley Business School

    Head, Practical Tools research group, Mistra Financial Systems (MFS) research consortium [5 projects, total funding: 58 million SEK ~ US$ 7 million]

    Member, Technical Expert Group on Sustainable Finance, DG FISMA, European Commission, EU

    Invited Fellow, Royal Society of Arts

    Inventor, US Patent 8751357 B1: investment performance measurement

    Prof. Andreas G. F. Hoepner is a CFDS and CSIF Program Lecturer at the DVFA.

    Full list of affiliations on LinkedIn 


    Prof. Borth, CFDS, DVFA

    Vita:

    2018 - today Professor of Artificial Intelligence & Machine Learning at University of St. Gallen

    2012 - today Co-Founder Sociovestix Labs – First in Financial Data Science

    2018 Deep Learning Research Amplitude Deep Learning Lab

    2015 - 2018 Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI)

    2016 - 2018 PI NVIDIA AI Lab (NVAIL)
    2016 - 2018 Director Deep Learning Competence Center
    2015 - 2017 Head of Multimedia Analysis & Data Mining

      Prof. Damian Borth is a CFDS Program Lecturer at the DVFA.

      Full list of affiliations on LinkedIn 

      Prof. Borth, CFDS, DVFA

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