MIT's Song Han launches Fall 2026 course on efficient ML, covering pruning, quantization and LLM deployment
HildeKuehne · x · 2026-10-11
MIT 6.5940, TinyML and Efficient AI Computing, is running for Fall 2026, taught by Song Han with Shang Yang, with lectures live-streamed and archived at efficientml.ai.
Topics span model compression, pruning, quantization, distillation, neural architecture search, distributed training, model serving and parallelism, gradient compression, and on-device fine-tuning, plus application-specific acceleration for LLMs and diffusion models. Students get hands-on experience deploying LLMs on a laptop. Classes meet Tue/Thu 4:00–5:30 PM ET; prerequisites are 6.191 and 6.390, and more lectures will be added over the semester.
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