8th Advanced Course on Data Science & Machine Learning

About

The 8th Advanced Course on Data Science & Machine Learning – ACDL 2025 is a full-immersion five-day Course at the Riva del Sole Resort & SPA (Castiglione della Pescaia – Grosseto – Tuscany, Italy) on cutting-edge advances in Deep Learning, Data Science and Generative AI with lectures delivered by world-renowned experts. The Course provides a stimulating environment for PhD students, Post-Docs, junior academics (only up to assistant professors), early career researches, and industry leaders (and highly motivated, promising and brilliant Master students / BSc students). Participants will also have the chance to present their results with talks, and to interact with their colleagues, in a convivial, professional and productive environment.
Language: English.

LECTURERS: https://acdl2025.icas.events/lecturers/
Each Lecturer will hold up to four lectures on one or more research topics.

Sanjeev Arora, Princeton University & Institute for Advanced Study, USA
Antoine Bosselut, EPFL, Switzerland
Sander Dieleman, Google DeepMind London, UK
Caglar Gulcehre, EPFL, Switzerland
Tatsu Hashimoto, Stanford University & Institute for Human-Centered Artificial Intelligence, USA
Thomas Hofmann, ETH Zurich, Switzerland
Subbarao Kambhampati, Arizona State University, USA
Joel Z. Leibo, Google DeepMind London & The Alan Turing Institute, UK
Lei Li, Language Technology Institute - Carnegie Mellon University, USA
Panos Pardalos, University of Florida, USA
Bryan Perozzi, Google Research, New York, USA
Raniero Romagnoli, Almawave, Italy
Liubov Tupikina, Bell Labs Paris, France

More Lecturers TBA

Lecturers: https://acdl2025.icas.events/lecturers/
Lectures: https://acdl2025.icas.events/lectures/

ACDL Schedule: https://acdl2025.icas.events/program/
https://acdl2025.icas.events/wp-content/uploads/sites/30/2024/12/ACDL-2025-Schedule.pdf

PAST LECTURERS: https://acdl2025.icas.events/past-lecturers/

To participate in the ACDL 2025, all attendants must

(1/2) register for the course (by February 23, 2025) and
(2/2) book accommodation at the course venue, “Riva del Sole Resort & SPA” (by April 23, 2025); all attendants must stay at the “Riva del Sole Resort & SPA”. Booking accommodation at the Riva del Sole must be made exclusively using the accommodation form attached to the registration confirmation email. No other methods must be used (if you use other booking methods the hotel will cancel the reservation). Finally, it is not possible to extend the stay, the special accommodation rates are valid only for the period of the course, no exceptions will be made. To contact the Riva del Sole Resort & SPA (the course venue) use the following email: booking.events@rivadelsole.it

Once accommodation has been booked at “Riva del Sole Resort & SPA“, the participant must send this information (including the Booking Number) to the ACDL organizing committee (acdl@icas.cc).

ACDL is a residential course, so all lecturers and participants must reside in the same Hotel (Riva del Sole Resort & SPA). No exceptions are made.

Course Registration and Fees
Early Registration Fee (by February 23, 2025): € 580
Late Registration Fee (from February 24, 2025): € 630

Course leader

Prof. Giuseppe Nicosia

Target group

PhD students, PostDocs, Industry Practitioners and Junior Academics (only up to assistant professors) will be typical profiles of the ACDL attendants.The Course will involve a total of 36–40 hours of lectures, according to the academic system the final achievement will be equivalent to 8 ECTS points for the PhD Students (and some strongly motivated Master Student – BSc Student) attending the Course.

Course aim

The lectures will be delivered by world renowned experts in the field, from both academia and industry, and will cover both theoretical and practical aspects of AI, Machine/Deep Learning, Generative AI, and Data Science.

ECTS Points

The Course will involve a total of 36-40 hours of lectures, according to the academic system the final achievement will be equivalent to 8 ECTS points for the PhD Students (and some strongly motivated master student) attending the course; during the course the PhD students will tackle home-works/projects.

Fee info