Over the last years, typical data science tasks like data manipulation and modelling have gained a stronger foothold in the day-to-day professional life of the actuary. Open-source languages are renowned to be especially equipped to deal with these kinds of tasks, but can also be tricky to get started with, especially when one has not been properly introduced to them. This workshop offers the opportunity to become more familiar with the open-source environment and its applications, illustrated in detail by means of a number of hands-on modules, thereby enabling the actuary to tackle the data science tasks in an elegant manner.

Open-source tools like R, Python and more recently Julia have gained a lot of momentum in recent years, not just in popularity but also in the amount of contributed code. Their respective communities are nowadays no longer exclusively composed of academic researchers and scientists, but also of professionals of all sorts of backgrounds, especially since the industry and corporate world have understood the added value of 'community driven software' and started to plug open-source tools into their processes and corporate tissue.

On top of this, actuaries are confronted with the same issues as academic researchers and scientists: the production of readable, shareable and reproducible code and results. In the actuarial community, R already is a fairly known and used open-source language, Python however a little bit less, even if it's also packed with potential and even if it disposes of a vast biosphere of its own. This workshop will also focus on the 'scientific stack' of both R and Python and draw some comparisons between both worlds where we will try to show that it's not a matter of choosing between both ecosystems but of choosing the best of both (continuously evolving) worlds.

Early-bird discount is available for bookings made by 18 August 2025.