Fall 2022 | Tuesdays & Thursdays, 3:30 – 5:00pm ET
Speaker: Song Han, MIT

Course will be streamed live on YouTube, with videos available afterwards.

Join this online course taught by MIT’s Song Han as we deep dive into efficient machine learning techniques that enable powerful deep learning applications on resource-constrained devices. Topics cover efficient inference techniques, including model compression, pruning, quantization, neural architecture search, and distillation; and efficient training techniques, including gradient compression and on-device transfer learning; followed by application-specific model optimization techniques for videos, point cloud, and NLP; and efficient quantum machine learning. Students will get hands-on experience implementing deep learning applications on microcontrollers, mobile phones, and quantum machines with an open-ended design project related to mobile AI.

Learn more about TinyML and Efficient Deep Learning.