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Organised by the EAA - European Actuarial Academy GmbH in cooperation with the Aktuarvereinigung Österreichs (AVÖ).
This is part four of four courses (seminar and exam) required to obtain the EAA Certificate in Actuarial Data Science. To earn the certificate, participants must complete all four modules, which include both the seminar and the exam. Members of AVÖ and/or DAV will obtain the additional title Certified Actuarial Data Scientist (by AVÖ and/or DAV) by fulfilling the same requirements. Furthermore, all courses are open to interested actuaries to deepen their knowledge and skills in the field of Actuarial Data Science (without exams).
Introduction
Due to technological progress in connection with Data Science and Digitalization, summarized under the buzzword Big Data, a plethora of opportunities and challenges for the industry is arising.
Technological developments have now also reached the insurance industry and thus have a direct impact on the working world of actuaries.
Under the heading Actuarial Data Science, the procedures and methods of data mining are embedded in the actuarial context. These range from mathematics-driven statistical methods for derivation of insights from data to computation-driven methods sometimes summarized as machine learning. As a result of almost unlimited computing capacity through cloud computing and wide availability of training data, tried and tested methods of machine learning, such as artificial neural networks, are experiencing a renaissance in theory and practice.
This web session is the fourth part of a four-part series at the German Actuarial Association (DAV). In this online training, we will expand on and deepen some of the topics already known from the basic, advanced and immersion seminar, discussing further important techniques in the context of deep learning and data storage. It is based on the learning objectives of the DAV for Actuarial Data Science Completion, which is part of the actuarial training in Germany.
In this three-day training, we deepen techniques and methods of (Actuarial) Data Science and take a rather theoretical tour to complete this course. We will cover important aspects of information theory from coding theory to web computing and close the mathematical foundations of deep learning. Along with insights in relevant aspects of insurance analytics we will investigate use cases in an insurance context. Finally, we will give a prospect of what is probably going to emerge in the future, namely quantum computing.
Early-bird discount is available for bookings made by 20 July 2026. |
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Coming soon... |
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FIDA for Actuaries: Challenge or Opportunity? | 18 May 2026
EAA e-Conference on Data Science & Data Ethics | 20 May 2026
Power Query, Power Pivot & Power BI for Actuaries | 15 June 2026
Explore our website for more information and discover all our upcoming events. For more insights, updates, and a bit of actuarial fun, feel free to follow us on LinkedIn! |