New Hands-on Online Course: Python

Originator and coach: Dr. Daniel J. Duffy, Datasim

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We are very pleased to announce a new online course (to commence 1 October 2019):

Distance Learning Applied Numerical Methods with Python and Python Libraries

Foundations for Computational Finance and Machine Learning

The goal of this hands-on course is to learn Python as a programming language (including object-oriented and functional programming (OOP/FP)) and then writing applications that use many of the Python libraries for numerical analysis,  data analysis, statistics and Machine Learning (ML). We then implement a number of PDE and Monte Carlo methods for computational finance using OOP/FP in combination with these libraries. We also give an introduction to several libraries for ML.

Last but not least, in order to ensure that programs avoid unstructured “big balls of muds” and descent into everlasting chaos (this is a real risk) we apply some proven best practices and processes that the course originator has applied in software projects. To this end, we introduce Design Patterns and we show how to implement them in Python. In this way we use standardized patterns whose use leads to maintainable software and keep software costs down.

This course is a multi-disciplinary approach to create software in well-defined steps, from the problem specification through to design and implementation in Python. We apply this process to computational finance but the method is universal. In short, we wish to write future-proof software.

Special features of the course are:

  • No-nonsense overview of  ‘essential Python’.
  • Object-oriented and functional programming in Python.
  • Writing flexible applications: enter Design Patterns.
  • Proactively learn Python libraries by ‘doing’. Understanding why and how algorithms work.
  • Designing and implementing applications in computational finance.
  • Interaction with supervisor (exercises, mini-project, certificate.)


No previous knowledge of Python is assumed but a degree or experience in a numerate field is advantageous.

The student price is Euro 1395 and 15% discount (Euro 1186) if you register before August 1 2019. If you live in EU VAT 21% needs to be paid. Outside EU no VAT.


The link to the course and further details can be found here:

Distance learning Applied Numerical Methods with Python and Python Libraries


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