The 18th edition of the Machine Learning and Advanced Statistics (MLAS) Summer School will take place in Madrid this June, offering an intensive two-week programme at the intersection of machine learning and modern statistical analysis. Co-organised by Pedro Larrañaga and Concha Bielza from the Universidad Politécnica de Madrid—both members of the ELLIS Unit Madrid—the school also features contributions from researchers such as Alberto Suárez and Daniel Hernández-Lobato from the Universidad Autónoma de Madrid, among others.
The programme includes 12 intensive courses of 15 hours each, delivered over two weeks. Participants can tailor their learning experience by selecting courses aligned with their interests, with the only constraint being that courses scheduled within the same time block cannot be taken simultaneously.
Designed for both students and professionals, the summer school combines strong theoretical foundations with hands-on practical applications. It aims to equip attendees with the tools needed to analyse and model complex datasets, while also fostering a deeper understanding of modern machine learning and statistical techniques.
With a clear focus on real-world relevance, MLAS addresses the growing demand for expertise in data science across academia and industry. At the same time, it remains accessible to participants from diverse backgrounds, encouraging interdisciplinary exchange and providing a solid foundation for applying these methods in a wide range of domains.
18th Machine Learning and Advanced Statistics Summer School
8–19 June 2026 · Madrid, Spain