An Introductory Course on Computational Artificial Intelligence Techniques for Engineering Students

This paper brings forth the design of an introductory course on computational artificial intelligence techniques for graduate and undergraduate engineering students.  The course is aimed at providing students outside the computer science and computer engineering curricula with an affordable and practical introduction to genetic algorithms, fuzzy logic, and artificial neutral networks.  At the end of the course, the students are expected to be able to solve engineering problems using the three covered methodologies.  The general strategy for designing the course aims at three main targets: readiness, practicality, and applicability.  Active and experiential learning methodologies are implemented primarily through three team projects addressing each of the three techniques investigated.  Students are directly involved in the selection of project topics to increase their motivation and participation and effectively close the gap between theory and practice in the context of applications that are relevant for student academic and career interests.  The course has been received with great interest by students and produced positive educational impact by allowing dissemination of powerful techniques to a broader engineering audience.

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