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The Train the Trainer Program is provided in conjunction with the regular AI and multi-GPU courses. This Train-the-Trainer program runs alongside the standard AI and multi-GPU computing courses. While the regular course focuses on practical skills for building and scaling AI workloads across multiple GPUs, the Train-the-Trainer track is dedicated to preparing future instructors to teach these topics effectively. 

Too few people are currently able to offer advanced AI and multi-GPU training at the level required by scientists, engineers, and PhD students who need to scale AI models efficiently or optimize distributed training workflows. Across Europe, only a limited number of HPC and AI centres provide such specialized courses. With this program, we aim to empower additional trainers and centres to deliver high-quality AI and multi-GPU training - either across Europe or within their own countries.

During this training event, participants will gain a deep understanding of modern multi-GPU and distributed AI technologies, along with practical techniques for teaching these concepts effectively. Expert instructors will guide attendees through state-of-the-art tools, frameworks, and best practices for scaling AI workloads, while also providing pedagogical strategies, teaching resources, and hands-on experience designed to prepare participants to deliver their own AI and multi-GPU training courses.

 

Instructors

Ashwin Mohanan (RISE)
Mats Sjoberg (CSC)
Caspar van Leeuwen (SURF)
Gyula Ujlaki (NCC Hungary)
Eleonora Bergamaschi (CINECA)
Michele Visciarelli (CINECA)
Prof. dr. Geert Jan Bex (UHASSELT)

Fees

Only participants from EuroCC/CoE/CASTIEL can take part in this course.

Pre-required logistics

You are familiar with AI frameworks.
<strong>Your centre is affiliated to one National Competence Centre (NCC) of </strong><a href="https://hpc-portal.eu/nccs&quot; target="_blank"><strong>EuroCC</strong></a><strong> or </strong><a href="https://hpc-portal.eu/coes&quot; target="_blank"><strong>CoEs</strong></a><strong>.</strong>