IST 663 - Machine Learning

[3 credit(s)]

Prerequisite: Completion of MIS preparatory program. This course will introduce machine learning methods, techniques, algorithms and use cases. It will offer a balanced approach to theory and practice by introducing the theoretical fundamentals and the computational artifacts to implement the machine learning algorithm using Python and MATLAB. The course will introduce a broad cross-section of models and algorithms spanning machine learning issues, both theoretical and practical covering topics such as statistical supervised and unsupervised learning methods, regression, regularization, neural network, Bayesian methods, kernel machines, reinforcement learning and deep learning. Sample data sets will be used to illustrate the course concepts by hands-on implementation with programming languages and tools.

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