Serving as an introduction to data mining algorithms and tools to solve engineering problems, this course emphasizes the knowledge discovery and mining of large scale datasets. This course is structured as a series of lectures and discussions that provide fundamental concepts and principles of knowledge discovery, computational intelligence, machine learning techniques, search mechanisms, statistical methods, probabilistic approaches, nearest neighbor and clustering methods, neural networks, kernel machines, genetic programming, hybrid intelligent systems, model validation and feature selection and ranking algorithms.
Please Note: Student participation is an essential part of the learning process; students will be expected to actively participate in the discussions.
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After completion of this course, students will:
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