Northern Arizona University 3 credits EE
This course covers hardware architectures for artificial intelligence and techniques to deploy AI algorithms on resource-constrained devices at the edge. Topics include neural network accelerator architectures, model optimization techniques such as quantization, pruning, and knowledge distillation, and deployment frameworks. Students implement AI inference pipelines on microcontroller platforms and evaluate performance tradeoffs related to latency, power consumption, and accuracy. Letter grade only.
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