Syllabus/Agenda
NOTE: Agenda is tentative and subject to change
Introduction
- Embedded AI Definition, Advantages, Challenges, and Applications
Core Concepts / Programming Frameworks / Platforms / Tools
- Fundamentals of Embedded Systems and AI/ML
- TinyML
- Machine Learning Sensors
- Hardware AI/ML Accelerators
- Embedded Data
- Federated Learning and Mobile AI
- Generative AI on the Edge
Applications in Embedded AI
- Acoustic AI
- Robotic AI
- Physical Knowledge-Informed AI
Hands-on Tutorials
- TinyML Image Classification, Object Detection, Keyword Spotting (Xiao ESP32S3 Sense)
- LLM/VLM on the edge (Raspberry Pi)
- Federated Learning (Flower)
Project
- Your turn!
Course Schedule (Subject to Change)
| Date | Topic |
|---|---|
| 1/26 | Course introduction and logistics (Fred Jiang) |
| 2/2 | Fundamentals of Embedded Systems and AI/ML (Fred Jiang) |
| 2/9 | TinyML (Fred Jiang) + TinyML (Tutorial 1) (TAs) |
| 2/16 | Extreme Edge (Vijay Janapa Reddi / Harvard) + student presentation |
| 2/23 | Embedded Wearable AI (Yang Liu / Florida State University) + student presentation |
| 3/2 | LLM Seurcity (Pan Hu / Uber) + student presentation |
| 3/9 | Health Intelligence (Bashima Islam / WPI) + student presentation |
| 3/16 | Spring Recess |
| 3/23 | LLM/VLM on the edge (Tutorial 2) |
| 3/30 | Small Multimodal Language Models (Mi Zhang / Ohio State University) + student presentations |
| 4/6 | TBD (Jorge Ortiz / Rutgers University) + student presentations |
| 4/13 | TBD (Ahmed Alsinan / Amazon) + student presentation |
| 4/20 | TBD (Nic Lane / Cambridge and Flower) + student presentations |
| 4/27 | Flower tutorial (William Lindskog / Flower Labs) |
| 5/4 | Project Demonstrations |