Actuarial Data Science Books / Lectures / Courses
We give an overview of lectures and courses in Actuarial Data Science which we consider to be useful for the profession.
Books in Actuarial Data Science
- Statistical Foundations of Actuarial Learning and its Applications, M.V. Wüthrich and M. Merz, 2023, Springer Actuarial
- Actuarial Data Science, M. Seehafer et. al., De Gruyter, 2021 (in German)
Lectures in Actuarial Data Science
- Data Analytics for Non-Life Insurance Pricing, ETH Zurich, M.V. Wüthrich and C. Buser
- Responsible Machine Learning with Insurance Applications, ETH Zurich, C. Lorentzen and M. Mayer
Courses in Actuarial Data Science
- Machine Learning with R for Actuaries, Swiss Association of Actuaries, M. Mayer, 2022, online
Deep Learning with Actuarial Application in R, Swiss Association of Actuaries, D. Meier, J. Schelldorfer and M.V. Wüthrich, 2020 & 2021, Zurich
- Insurance Data Science: Use and Value of Unusual Data, University of Lausanne and Swiss Association of Actuaries, J.-P. Boucher, A. Charpentier and Ewen Gallic, 12th - 16th August 2019. The slides and the code are publicly available here.
- Insurance Analytics, A Primer, University of Lausanne and Swiss Association of Actuaries, M. Denuit and J. Trufin, 13th-17th August 2018. (The course slides are not publicly available, so please contact the lecturers for providing you the slides. The exercises are publicly availabe on GitHub).
Courses in Actuarial Science with "a Data Science touch"
We see the following lectures / courses / books in the traditional area of actuarial science, but having a "Data Science touch":
- Computational Actuarial Science with R, CRC Press, A. Charpentier.