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](https://ece.duke.edu/wp-content/uploads/sites/9/2024/07/AdobeStock_224585219-scaled.jpeg)
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.
Requirements
Note: The ECE major requirement being fulfilled appears in square brackets: […].
No course may be used to fulfill more than one requirement.
- ECE 480: Applied Probability for Statistical Learning
[ECE Concentration Elective #1—Signal Processing, Communications and Control Systems (SPC&C)] - ECE 580: Introduction to Machine Learning
[ECE Concentration Elective #2—SPC&C] - 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
- 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
- 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