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Courses / Graduate School / ECE

ECE 587 · also STA 563

Information Theory

Galen Reeves

Description from DukeHub

Information theory is the science of processing, transmitting, storing, and using information. This course provides an introduction to mathematical measures of information and their connection to practical problems in communication, compression, and inference. Entropy, mutual information, lossless data compression, channel capacity, Gaussian channels, rate distortion theory, Fisher information. Useful for researchers in a variety of fields, including signal processing, machine learning, statistics, and neuroscience. Appropriate for beginning graduate students in electrical engineering, computer science, statistics, and math with a background in probability.

Skills

AI-resilient: 0 of 5

  • No: Physical, lab or field work
  • No: Live work with people
  • 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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