Concentration in Machine Learning

Earn a transcript notation without completing additional courses

Focus your course selection by following a defined thematic pathway within the ECE major.

abstract image of brain with neural networks

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.

Successful completion of all requirements will result in a designation of “Concentration in Machine Learning” on your official transcript.

Declare Concentration

Select this option on the Declaration of Major form.

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Requirements

Note: 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 661: Computer Engineering Machine Learning & Deep Neural Networks
    • ECE 662: Machine Learning Acceleration & Neuromorphic Computing
    • ECE 663: Machine Learning in Adversarial Settings
    • ECE 682D/CS 571/Stat 561: Probabilistic Machine Learning
    • ECE 684: Natural Language Processing 
    • ECE 685D: Deep Learning
    • ECE 687D/CS 671D/Stat 671D: Machine Learning
    • ECE 495/590: Special Topic courses on Machine Learning that are approved area of concentration electives (with DUS approval)
      • ECE 495.01 (F24): Introduction to Natural Language Processing 
  4. One of the following
    [ECE Free Elective]:
    • ECE 588: Image & Video Processing
    • ECE 661: Computer Engineering Machine Learning & Deep Neural Networks
    • ECE 662: Machine Learning Acceleration & Neuromorphic Computing
    • ECE 663: Machine Learning in Adversarial Settings
    • ECE 682D/CS 571/Stat 561: Probabilistic Machine Learning
    • ECE 684: Natural Language Processing 
    • ECE 685D: Deep Learning
    • ECE 687D/CS 671D/Stat 671D: Machine Learning
    • ECE 689/CS 676: Advanced Topics in Deep Learning
    • ECE 495/590: Special Topic courses on Machine Learning (with DUS approval):
      • ECE 590 (S23): Brain Computer Interfaces
      • ECE 495.01 (F24): Introduction to Natural Language Processing  
  5. One of the following
    [ECE Extension Elective]:
    • ECE 588: Image & Video Processing
    • ECE 661: Computer Engineering Machine Learning & Deep Neural Networks
    • ECE 662: Machine Learning Acceleration & Neuromorphic Computing
    • ECE 663: Machine Learning in Adversarial Settings
    • ECE 682D/CS 571/Stat 561: Probabilistic Machine Learning
    • ECE 684: Natural Language Processing 
    • ECE 685D: Deep Learning
    • ECE 687D/CS 671D/Stat 671D: Machine Learning
    • ECE 689/CS 676: Advanced Topics in Deep Learning
    • ECE 495/590: Special Topics courses on Machine Learning (with DUS approval):
      • ECE 590 (S23): Brain Computer Interfaces
      • ECE 495.01 (F24): Introduction to Natural Language Processing  
    • 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
    • ME 555 (F23): Robot Learning 
    • BME 590 (F23): Machine Learning in Pharmacology