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Michael Richard Gustafson
mrg@duke.eduDirector of Undergraduate Studies, Associate Professor of the Practice of ECE
Now more than ever, writing savvy code and understanding the abilities and limits of AI touches just about every industry there is. And we’re not hoarding our secrets. To empower a broad range of Duke graduates with the skills that today’s top employers are looking for, we offer invaluable minors in ECE as well as Machine Learning & AI.
The latter is available to ECE majors, too (although a concentration in machine learning is likely a better option), and both can be an excellent complement to another major and provide a new layer of knowledge and expertise.
The minor in ECE requires a minimum of five technical courses. Three courses must be drawn from the set of “core courses” required of all ECE majors and two must be upper-level ECE courses.
Core courses (choose 3): ECE 110L (Fundamentals of ECE), ECE 230L (Microelectronic Devices & Circuits), 250D (Computer Architecture), 270DL (Fields & Waves), and 280L (Signals & Systems)
Upper-level courses (2): Two ECE courses at or above the 300-level
Courses that are used to fulfill the student’s major(s) may not be double-counted toward the minor. In addition, ECE courses with content substantially equivalent to courses in the student’s major(s) may not be counted toward the minor.
It is expected that a student pursuing a minor in ECE will satisfy all pre-requisites for each course selected for their minor program. This will typically involve completion of courses in Math, Physics and/or Computer Science, which are pre-requisites for many of the core ECE courses.
Students interested in pursuing a Minor in ECE are advised to discuss their plan of study with the Director of Undergraduate Studies in ECE.
The Minor in Machine Learning & Artificial Intelligence requires the completion of a minimum of five (5) technical courses.
This education offering is an outgrowth of Duke ECE’s global research leadership in AI and machine learning.
To provide sufficient foundational breadth, three (3) courses are drawn from identified core areas fundamental to the discipline. Students tailor their course of study through selecting two (2) upper-level (300-level or above) focus courses.
Required
Choose two (2)
It is expected that a student pursuing a Minor in Machine Learning & Artificial Intelligence will satisfy all prerequisites for each course selected for their minor program.
This will typically involve completion of courses in Math, Statistics, and Computer Science, which are pre-requisites for the fundamental and elective courses.
Specifically, the following prerequisite knowledge is assumed:
Exceptions may be granted by the Director of Undergraduate Studies in ECE, for example, if a student’s preparation is deemed equivalent to the pre-requisite.
Director of Undergraduate Studies, Associate Professor of the Practice of ECE
Associate Director of Undergraduate Studies, Assistant Professor of the Practice in the Department of ECE