Concentration in Machine Learning

Complete five courses—Earn a notation on your Duke transcript

Students pursuing a major in ECE may focus their course selection within the major by following a defined thematic pathway within the major.

Successful completion of all requirements will result in a designation of "Concentration in Machine Learning" on the official transcript.

The Concentration in ML does not require additional courses

ECE majors can declare this concentration by selecting this option on the Pratt Declaration of Major form.

Completion of the Concentration in Machine Learning requires a minimum of 5 courses.

These requirements can be met within the general requirements of the ECE major and do not require any additional courses; however, the choice of classes has been constrained to fit the Concentration requirements.


Requirements

Notes

  • The ECE major requirement being fulfilled appears in square brackets [...]
  • No course may be used to fulfill more than one requirement

 

1.  ECE 480: Applied Probability for Statistical Learning

[ECE Concentration Elective #1—Signal Processing, Communications and Control Systems (SPC&C)]

2.  ECE 580: Introduction to Machine Learning

[ECE Concentration Elective #2—SPC&C]

3.  One of the following

[ECE Area of Concentration Elective #3—any area, including SPC&C]:

  • ECE 588: Image & Video Processing
  • ECE 682D/CS 571/Stat 561: Probabilistic Machine Learning
  • ECE 685D: Deep Learning
  • ECE 687D/CS 671D/Stat 671D: Machine Learning
  • ECE 590: Special Topic courses on Machine Learning that are approved area of concentration electives (with DUS approval)

4.  One of the following

[ECE Free Elective]:

  • ECE 588: Image & Video Processing
  • ECE 682D/CS 571/Stat 561: Probabilistic Machine Learning
  • ECE 685D: Deep Learning
  • ECE 687D/CS 671D/Stat 671D: Machine Learning
  • ECE 590: Special Topic courses on Machine Learning (with DUS approval)

5. One of the following

[ECE Extension Elective]:

  • ECE 588: Image & Video Processing
  • ECE 682D/CS 571/Stat 561: Probabilistic Machine Learning
  • ECE 685D: Deep Learning
  • ECE 687D/CS 671D/Stat 671D: Machine Learning
  • ECE 590: Special Topics courses on Machine Learning (with DUS approval)
  • CompSci 371: Elements of Machine Learning
  • CompSci 527: Computer Vision
  • Math 465/CompSci 445: Introduction to High Dimensional Data Analysis
  • Stat 340: Introduction to Statistical Decision Analysis
  • Stat 360: Bayesian Inference and Modern Statistical Methods