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Courses and Events

The Datasim range of courses in Quantitative Finance have been designed for those professionals who model and develop derivatives products using robust and accurate numerical methods and who deploy the resulting algorithms in powerful object-oriented languages such as C++ and C#. Datasim is one of the few training institutions that can offer a number of courses on topics that are of vital importance in quantitative finance:

  • The Finite Difference Method (FDM) for one, two and three factor derivative modeling
  • The Monte Carlo method and simulation techniques for multi-factor problems
  • Numerical Methods for Quantitative Analysts
  • Introductory and Advanced C++ courses for finance
  • Multi-threaded and parallel processing in C++
  • C# for Computational Finance Applications


We give these courses in various venues throughout the world, for example, London, New York City and Frankfurt. Another popular option is "in-company" courses where our courses can be given at your company's premises or alternatively a customized course based on your specifications.  Once you have finished our course you can avail of the free forums at the Datasim web site to ask questions on the course, download relevant code and communicate with other course attendees.

These courses were developed by Dr. Daniel J. Duffy, an internationally known trainer, Wiley author and practitioner of numerical methods in C++ for derivatives pricing. He is the author of three popular books on finance.

 

Distance Learning Courses

RegisterDistance Learning Course
Any time
(Distance learning)
Distance Learning - Computational and Quantitative Finance in C++ (full course)
Any time
(Distance learning)
Distance Learning - Computational and Quantitative Finance in C++ (modules 4 - 10)
Any time
(Distance learning)
Distance Learning - Advanced Finite Difference Method (FDM) for Computational Finance
Any time
(Distance learning)
Distance Learning - Advanced C++ - Programming Models, boost and Parallel Computation
Any time
(Distance learning)
Distance Learning - Advanced C# for Computational Finance and Derivatives' Pricing
Any time
(Distance learning)
Distance Learning - C++ and its Application in Finance
Any time
(Distance learning)
Distance Learning - Creating Add-in Excel Applications using C++ and C#; Interoperability Software Tools and Applications
Any time
(Distance learning)
Distance Learning - Numerical Methods for Computational Finance, Engineering and Science
Any time
(Distance learning)
Distance Learning - Mathematics Foundations course
Any time
(Distance learning)
Distance Learning - Computational and Quantitative Finance in C++ 11

Note: The distance learning courses can start at any time.

Regular Scheduled Courses

Date / durationCourseLocation
Nov 01 - Nov 03 2017
(3 days)
Advanced C# for Computational Finance and Derivatives' Pricing Amsterdam
(The Netherlands)
Nov 14 - Nov 17 2017
(4 days)
Advanced C++ and C++ 11: The new Standard Amsterdam
(The Netherlands)
Jan 23 - Jan 26 2018
(4 days)
Advanced Finite Difference Method for Quantitative Finance: Theory, Applications and Computation London
(United Kingdom)
Feb 07 - Feb 09 2018
(3 days)
Advanced C# for Computational Finance and Derivatives' Pricing Amsterdam
(The Netherlands)
Feb 13 - Feb 16 2018
(4 days)
Advanced C++ and C++ 11: The new Standard London
(United Kingdom)
Apr 03 - Apr 06 2018
(4 days)
Advanced Finite Difference Method for Quantitative Finance: Theory, Applications and Computation Frankfurt
(Germany)
Apr 24 - Apr 27 2018
(4 days)
Advanced C++ and C++ 11: The new Standard Datasim, Amsterdam
(The Netherlands)
May 09 - May 11 2018
(3 days)
Advanced C# for Computational Finance and Derivatives' Pricing London
(United Kingdom)
Jun 12 - Jun 15 2018
(4 days)
Advanced C++ and C++ 11: The new Standard New York
(United States)

Courses on request

Course
Advanced C++ and Boost C++ Libraries and Applications to Computational Finance
Creating Add-in Excel Applications using C++ and C#; Interoperability Software Tools and Applications
Numerical Methods for Computational Finance, Engineering and Science