ECE 210Brain-Inspired Machine Learning
Studies how the computational principles of the brain can be applied to build efficient machine learning models in software and hardware. Topics include the neuroscience of deep learning, spiking neural networks, hardware accelerators, and memory circuit design. Taught in conjunction with ECE 110. Students cannot receive credit for this course and ECE 110.
Enrollment is restricted to graduate students.
- Taught in conjunction with ECE 110.
Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.
When it runs
Fall 2026Open Fall 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 5:20pm–6:55pm | PhysSciences 136 | J. Eshraghian | Wait List 20/20 |
Winter 2026Open Winter 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 5:20pm–6:55pm | PhysSciences 110 | J. Eshraghian | Open 31/35 |
Fall 2025Open Fall 2025
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Asynchronous | — | Staff | Closed 0/45 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Jason Eshraghian | 4.3 / 5 | 2.2 / 5 | 83% | 6 |
From RateMyProfessors, which is student-submitted and not a survey. Small review counts move a long way on one bad quarter.
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