This course includes in-depth coverage of existing and emerging IoT application domains, machine learning and deep neural networks, GPU and FPGA programming, optimization techniques for deep learning acceleration, and various computing systems that facilitate the rapid realization and growth of IoT. Detailed topics include the definition and characteristics of IoT; IoT enabling technologies; smart domains and applications; IoT systems; IoT design methodology; machine learning and deep learning; embedded GPU and FPGA for IoT; IoT servers and cloud; data analytics for IoT; cognitive computing; cognitive systems design; cognitive application workload; IoT security; hands-on learning experience to build IoT systems; and various case studies such as smart home and IoT for healthcare.
Machine problems working with Raspberry Pi, edge TPU, and cloud computing, together with homework assignments will be given to reinforce students' understanding and learning of the techniques and topics.
Lecture Time: Tuesdays and Thursdays 11 am - 12:20 pm
Lecture Location: 1310 Digital Computer Laboratory
Lab Location: 4022 Electrical & Computer Eng Bldg
Click here to access the syllabus.
- Professor Chen: Tuesdays 4:00 pm - 5:00 pm at CSL 250
- Neo Yuan: Mondays 3:00 pm - 4:00 pm at ECEB 4022
- Yuhong Li: Tuesdays 9:00 am - 11:00 am at ECEB 4022
- Greg Jun: Thursdays 2:00 pm - 3:00 pm at CSL 403
- Junhao Pan: Fridays 10:00 am - 12:00 pm at ECEB 4022
- Session 1: Mondays 10 am - 11:50 am. TA: Junhao Pan
- Session 2: Mondays 1 pm - 2:50 pm. TA: Neo Yuan, Greg Jun
- Session 3: Mondays 4 pm - 5:50 pm. TA: Yuhong Li
- Lab 1 document: Lab 1
- Demo: Mon, Feb 13, in your lab sessions; Report due: Tues, Feb 14, 11:59 PM.
- Jan 23 Lab slides: Slides
- 02/04 Homework 1 is released
|Jan. 17||Lecture 01: Course Introduction||[slides]|
|Jan. 19||Lecture 02: Introduction to IoT programming||[slides]|
|Jan. 24||Lecture 03: Introduction of Cognitive Computing and ML||[slides]||[recording]|
|Jan. 26||Lecture 04: IoT Enabling Technologies and IoT Devices||[slides]||[recording]|
Q & A
We use Piazza for Q & A.