Detailed Course Information |
Fall 2026
Nov 02, 2026 |
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| CMAI 360 - Machine Learning |
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Fundamental principles and core algorithms of machine learning, including supervised and unsupervised learning such as linear and logistic regression, decision trees, Bayesian inference, support vector machines, neural networks, and clustering methods. The course emphasizes model design, training, evaluation, optimization, and practical deployment considerations. Hands-on experience in designing, implementing and evaluating machine learning applications.
0.000 TO 3.000 Credit hours 0.000 OR 3.000 Lecture hours 0.000 TO 2.000 Lab hours Levels: Undergraduate Schedule Types: Lab, Lecture Computer Science & Engineering Department Course Attributes: Engineering Course (TUI) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Must be enrolled in one of the following Colleges: Engineering Prerequisites: Undergraduate level GENG 200 Minimum Grade of D and (Undergraduate level CMPS 303 Minimum Grade of D or Undergraduate level CMPS 360 Minimum Grade of D) |
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