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On 19/03/2020 in Brussels:
Reserving Analytics (3 CPD) : POSTPONED !
Because of the current outbreak of the corona covid-19 virus in Belgium it has been decided to cancel the training until further notice.
We will keep you informed as soon as a new date is available.
Thanks a lot for your understanding.
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On 10/03/2020 in Brussels:
Pricing Analytics (3 CPD)
In this workshop you will develop a fully data driven strategy to incorporate factor information, continuous risk factors and geographical information in an insurance tariff.
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On 01/01/2020 in Brussels:
Corporate Governance of Insurance Companies (Sessies in het Nederlands) (2CPD / sessie)
What every (future) Director should know ...
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On 01/01/2020 in Brussels:
Corporate Governance of Insurance Companies (Sessions en français) (2 CPD/session)
What every (future) Director should know ...
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On 05/12/2019 in Brussels:
General Assembly IA|BE: 05/12/2019
You are kindly invited to attend our next Annual Assembly and the visit of the exposition 'Beyond Bruegel' which will take place on Thursday 5 December 2019 as from 18:00 on.
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On 04/12/2019 in Brussels:
ECA 2019 Papers (1.50 CPD)
In this session, three papers of the 3rd European Congress of Actuaries, held in June 2019, will be presented.
Participation is free !
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On 21/11/2019 in Brussels:
Pensions in Perspective (Speakers: Jan De Bondt & Wim Vermeir) (2 CPD)
This session is part of the PENSION sessions.
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On 12/11/2019 in Brussels:
Forum IA|BE: Emerging Roles for Actuaries (3 CPD) : 12/11/2019
What does the future hold for actuaries?
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On 15/10/2019 in Brussels:
R - Python - Open Source (Speakers: Luc Kesters & Robin Van Oirbeek) (15 CPD)
In five sessions the basic principles of R, Python and Open Source ( data visualisation, data manipulation, advanced data structures, automatic reporting, app building, ...) will be explained, completed with some exercises.
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On 26/09/2019 in Brussels:
Deep learning in Insurance (Speaker: Robin Van Oirbeek) (7.50 CPD)
In three sessions an introduction to Deep Learning (DL), a deep dive into the important technical details, an introduction to how to fine tune a Deep Learning model as well as an application of the DL methodology on insurance data will be discussed.