Built for engineers, researchers, and teams who want more than theory. Each program blends essential concepts with real ML-to-hardware workflows, covering every step from model training to optimized edge deployment.
Bridging the gap between software algorithms and hardware acceleration through hands-on learning.
Foundational modules connecting ML concepts with real hardware constraints. Understand how memory, dataflow, and parallelism shape the performance of Edge AI systems without touching a board yet.
Entry levelAn intensive 2-week guided lab covering the complete workflow: from training and model optimization to IP core generation and FPGA deployment. Practice-first learning using the KalEdge methodology.
Intermediate · 2 WeeksTailored training programs for universities, research labs, and engineering teams. We adapt the syllabus to your specific hardware targets and accelerate your team's research-to-hardware iteration cycle.
Advanced · Cohort-basedWe partner with universities and research labs to accelerate their Edge AI initiatives.
Delivered an intensive training program for researchers and engineers at UCLM. The collaboration focused on bridging the gap between theoretical Machine Learning and practical hardware deployment, utilizing our end-to-end Edge AI workflows.