Registrations are open for MaLGa – Machine Learning Genoa Center's 2024 Summer School, PhD courses open to students, postdocs and faculty from any university, as well as professionals:

  • Deep Learning and Computer Vision (DLCV)
    The third edition of the DLCV School, merging two crash courses, provides a hands-on introduction to basic principles of deep learning, computer vision, and their strong interconnection. Besides the analysis of well-established approaches, the course will highlight current trends and open problems.
    Submit application deadline: Monday, April 1, 2024
  • Machine Learning Crash Course (MLCC)
    MLCC was held for the first time in 2014 and has evolved into different formats since then, attracting more and more students from all over Europe. It introduces the fundamental methods at the core of modern Machine Learning, covering theoretical foundations as well as essential algorithms.
    Submit application deadline: Monday, April 1, 2024
  • Applied Harmonic Analysis and Machine Learning (AHAML)
    This fifth edition of AHAML consists of three courses on applied harmonic analysis and machine learning. The lecturers will be Karlheinz Gröchenig (University of Vienna), Alberto Setti (University of Insubria) & Davide Bianchi (Sun Yat-sen University) and Irène Waldspurger (CNRS). We will also host a one-day workshop with invited speakers and selected contributed talks/posters from the participants.
    Registration deadline: Wednesday, July 31, 2024

The maximum number of participants for each school is 120

All schools will include lectures and hands-on lab activities, and are open to students, postdocs and faculty from any university, as well as professionals. We won't miss the chance to offer fun and educational activities during our schools: seminars, workshops, poster sessions, an aperitif to get to know each other better…Read all the details about each specific course at MaLGa webpage, and find out how to apply!

The summer schools are part of the Boosting PhD students' careers activities of the RAISE training programme. The course aims to promote transversal training activities for students on PhD courses in the AI and Robotics fields, aimed at fostering the acquisition of specific skills for scientific research and transversal skills, in addition to disciplinary ones, to facilitate entry into the world of work.