Detailed Course Information |
Summer 2026
Aug 30, 2026 |
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| INT 3043 - Introduction to Machine Learning |
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This class is an introductory undergraduate course, and it provides a broad introduction to machine learning algorithms, principles, models and techniques. It covers topics in learning theory, dimension reduction, classification, clustering, Bayesian theory, support vector machines, neural networks, deep learning, and reinforcement learning. The course is a programming-focused introduction to Machine Learning and students will gain practical experience by conducting a project and using the algorithms and methods introduced in the course to solve real-world problems. By the end of the course, students will have developed practical skills in building learning models, deploying and evaluating their performances.
3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate, Undergraduate Schedule Types: Lecture Academic Division Management Department Course Attributes: CoBIT - Junior Prerequisites: Undergraduate level INT 2103 Minimum Grade of D- and Undergraduate level INT 2113 Minimum Grade of D- and Undergraduate level INT 2114 Minimum Grade of D- and Undergraduate level MCS 2124 Minimum Grade of D- |
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