IA|BE is organizing for 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 3: Advanced topics in Machine learning
This module extends on the learnings from the two previous modules to introduce transparency and ethics in machine learning models.
The importance and choice of variables, their (additive) contributions to the model's behavior and causal relations will be explored.
The last session will invite a panel of speakers to present new topics of interest in the machine learning community, of relevance for the actuarial community.
This session concludes by opening perspective on the problems modern machine learning can tackle, beyond classification and regression problems.
- 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 3 : Advanced topics in Machine Learning
|Day 1, Wednesday 5 October|
|16:00 - 18:00||Global & Local interpretation of Machine Learning models. By HAINAUT Donatien|
|Day 2, Wednesday 12 October|
|16:00 - 18:00||Programming : Interpretability tools|
|Day 3, Wednesday 19 October|
|16:00 - 18:00||Variable selection and model agnostic methods By VAN OIRBEEK Robin|
|Day 4, Wednesday 26 October|
|16:00 - 18:00||Programming : Putting models in production (Part I)|
|Day 5, Wednesday 2 November|
|16:00 - 18:00||Causality and Ethics in Machine Learning|
|Day 6, Wednesday 9 November|
|16:00 - 18:00||Programming: Putting models in production (Part II)|
|Day 7, Wednesday 16 November|
|16:00 - 18:00||New advances in Machine Learning|
|Day 8, Wednesday 23 November|
|16:00 - 18:00||Wrap-up & Case study on ethics and fairness|