Courses & Programs
KaleidoForge courses are 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 on FPGA and embedded platforms.
All courses include some level of FPGA interaction, from simple board demos to hands-on experiments, ensuring every participant gains real hardware intuition.
Program Tracks
You can follow a single track or combine them depending on your context.
Core Foundations
Foundational modules connecting ML concepts with real hardware constraints: memory, dataflow, and parallelism.
Entry level · FPGA demo intuition included
Request syllabusML-to-FPGA Essentials
Your first practical steps into ML-FPGA integration. Learn how a neural network becomes hardware and how compute blocks, DSPs, and on-chip memories shape performance.
Beginner · includes introductory board experiments
Request syllabusFull Pipeline Integration
End-to-end workflow: training → optimization → IP core → firmware → deployment. Ideal for teams aiming to understand the complete ML-hardware path.
Intermediate · reproducible FPGA deployments
Request syllabusAdvanced Optimization & Acceleration
Deep dive into performance-critical techniques: quantization, pruning, distillation, fusion, profiling, and hardware-aware benchmarking.
Advanced · includes hardware-ready demos
Request syllabusHands-On FPGA Lab (Cohort)
A fully guided, practice-first program. Real FPGA boards, experiments, debugging sessions, and direct mentoring.
Cohort-based · intensive board labs
Request cohort infoWhat's the Difference?
We offer two intensive 2-week programs with different goals:
2-Week Full Pipeline
Learn the full ML-to-hardware workflow. FPGA is the final deployment target, not the main learning tool.
- Training → optimization → IP core → firmware → deployment
- Structured, reproducible examples
- Methodology-focused
- FPGA: light usage (demo/deployment)
2-Week Guided Lab
A fully hands-on FPGA experience. The board is the primary learning environment.
- Board experiments & mini-projects
- Hardware debugging & troubleshooting
- Practice-first learning
- FPGA: heavy usage (daily experiments)
Format & Delivery
Programs offer a balance of clarity, hands-on practice, and real FPGA interaction. Every format includes hardware exposure.
- Live online sessions with Q&A
- Short 3-day modules (concepts, dataflow, optimization, ML-FPGA basics)
- 1-week hands-on workflow: training → optimization → FPGA deployment
- 2-week Full Pipeline: method-focused, light FPGA use
- 2-week Guided Lab: intensive FPGA practice
- Optional KalEdge Studio integration
- 4–6 week blended formats for universities and research labs
Who It’s For
KaleidoForge courses are ideal for engineers and researchers working on ML, embedded AI, or FPGA acceleration.
- Engineering teams bringing ML models to hardware or edge platforms
- Research labs in efficient AI or embedded systems
- R&D teams optimizing latency and power
- Engineers wanting to understand the ML-to-hardware journey
Enroll or Design a Custom Program
If you’d like to join a cohort or design a program aligned with your projects, reach out.
Share your context (academic/industry, team size, goals) and we’ll recommend the right structure.
Contact for syllabus & dates