Basic probability (ECE 313 or equivalent), introductory knowledge of machine learning or instructor’s consent, and basic computer systems knowledge.
We will compute the final grade using the following table:
Activity | Grade | Details |
---|---|---|
Paper Reviews | 10% | |
Student-led Presentation and Discussion | 15% | |
Class Participation | 5% | |
In-class Design Innovation Activity | 30% | |
Course Project | 40% | Proposal (3%) + Prelim Presentation (7%) + Mid-term Report (10%) + Final Report (10%) + Final Presentation (10%) |
The instructors will use Campuswire as a medium for paper discussion. For each regular class, students who are not presenting in that session are expected to write short reviews for the papers being presented by 10:00pm the night before the class. Please try to engage in a discussion with your classmates instead of summarizing the paper.
The final project is an open-ended research project that can target the design, development of reliable systems and networks. Projects dealing with evaluation of systems reliability using analytical models or measurements are also encouraged. We will also provide a list of project topics for reference, but you are free to come up with your own ideas.
Students will form groups of two or three for the final project early in week 3. One member of each project team should signup the team at this (link TBD) by (date TBD) before the start of the class. We will also initiate a Campuswire post to help you in team search. Failure to form project group by the deadline will lead to TA assigning the student to a group.
To be announced.