IA|BE is organizing for the second time a training program that will offer the possibility to obtain a certificate: the IA|BE Actuarial Data Scientist Certificate.
The objective of the training is to provide to the participants a deep understanding of key Data Science methods, their domain of applicability, key results of interest for practitioners and connections with the classical actuarial methods.
Moreover, the program emphasizes on applied programming practice and demystifies concepts such as model deployment in a corporate environment, MLOps, Object-Oriented programming, code management tools (e.g. Github), and principles of software engineering. For this purpose, Python has been chosen as programming language.
The program consists of 3 modules, each of which is followed by an assignment.
Each module consists of 4 theory sessions and 4 programming sessions.
The theory sessions will be given by the professors of the KU Leuven, UC Louvain and Université Libre de Bruxelles.
For the programming sessions, the Board of IA|BE has decided to cooperate with Reacfin and a team of KU Leuven affiliated researchers in (insurance) data science, coordinated by prof. K. Antonio.
Participants who successfully complete the 3 modules will receive the Certificate of IA|BE Actuarial Data Scientist.
Each of these modules can also be taken separately.
Module 1: Statistical foundations of machine learning
This module encompasses some of the classical actuarial methods such as (generalized) linear models to introduce classification and regression problems.
This module strengthen the actuarial background and develops the (generalized) linear models up to an overview modern deep learning, gradually introducing key machine learning concepts.
- When registering for the full programme of 3 Modules : 800 € / Module
- Otherwise : 1 000 € / Module
The sessions will be set up online.
In order to guarantee optimal training conditions and interactivity of the programming sessions, the number of participants is currently limited to 20.
Schedule of Module 1: Foundations of Machine Learning in Actuarial Sciences
|Day 1, Thursday 3 February|
|16:00 - 18:00||Linear Models and conditional expectation By ANTONIO Katrien|
|Day 2, Thursday 10 February|
|16:00 - 18:00||Programming : Foundations of actuarial learning and the organization of the training|
|Day 3, Thursday 17 February|
|16:00 - 18:00||Generalized Linear Models: regression and classification By ANTONIO Katrien|
|Day 4, Thursday 24 February|
|16:00 - 18:00||Programming : LMs and GLMs|
|Day 5, Thursday 10 March|
|16:00 - 18:00||Regularisations and links with other support vector machines By ANTONIO Katrien|
|Day 6, Thursday 17 March|
|16:00 - 18:00||Programming : Regularization|
|Day 7, Thursday 24 March|
|16:00 - 18:00||Neural Networks By ANTONIO Katrien|
|Day 8, Thursday 31 March|
|16:00 - 18:00||Programming : Deep Learning|
|18:00 - 23:59||Assignment after Module 1|