Edge AI & TinyML Courses

Edge AI runs machine learning models directly on devices like smartphones, microcontrollers, and IoT sensors instead of in the cloud. This reduces latency, improves privacy, and enables offline operation.

TinyML focuses on running ML models on ultra-low-power microcontrollers with limited memory and compute. It enables AI applications in wearables, smart sensors, and battery-powered IoT devices.

Techniques include quantization (reducing precision), pruning (removing unnecessary weights), knowledge distillation (training smaller models from larger ones), and architecture search for efficient designs.

Popular platforms include NVIDIA Jetson for GPUs, Coral Edge TPU for accelerated inference, Arduino and ESP32 for TinyML, and smartphones with built-in neural processing units (NPUs).