Hands-on, hardware-aware workshops focused on HLS, FPGA deployment, and ML acceleration.
An in depth workshop focused on reducing model size and latency for Edge AI applications. Master techniques like quantization, pruning, knowledge distillation, and low rank factorization to achieve highly efficient models.
November 4, 11, 18 and 25, 2026 · Four sessions × 2 hours · Time to be announced · Online
More InfoAn end-to-end hands-on tutorial presented at the FastML 2026 conference, demonstrating our unified KalEdge workflow from dataset loading to hardware execution on the HyperFPGA cluster.
August 2026 · Live Tutorial
View ResourcesA practitioner-oriented, experience-based introduction to deploying Machine Learning models on FPGAs, covering the complete ML to hardware workflow.
March 21 & 28, 2026 · Two sessions × 3 hours · 16:00–19:00 CET · Online