ECE 487
System Design for Machine Learning and Signal Processing
Henry Pfister
Description from DukeHub
Small groups work through design process for a machine learning &/or signal processing system. Brainstorming ideas, reviewing modern techniques in ML & SP, choosing & implementing projects. Use of modern collaboration tools & techniques that allow agile collaborative group design & development, consideration of resources, delivery of written & oral presentations, consideration of appropriate engineering standards & realistic constraints. Prerequisites: ECE 230L & 250D & 270DL & 280L & (MATH 353 or 356) & (STA 240L, MATH 230, 231, 238L or 340, ECE 555 or EGR 238L) & (PHYSICS 26 or 152L) & (CHEM 101DL, 20 or 21) & two Signal Processing, Communication & Controls concentration electives.
Skills
- programmingdepartment: ECE
- ai and machine learningtitle: "machine learning"
- designtitle: "design"
- public speakingAI review: "delivery of written & oral presentations"
- writingAI review: "delivery of written & oral presentations"
AI-resilient: 1 of 5
- No: Physical, lab or field work
- Yes: Live work with people · "collaboration"
- No: Judgment someone is accountable for
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
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