CEE 1323 - PRACTICAL DATA SCIENCE AND MACHINE LEARNING
Minimum Credits: 3
Maximum Credits: 3
This course will introduce data science and machine learning concepts to engineering students and professionals with emphasis on practical engineering applications. Key approaches and techniques for working with applied data science and machine learning with many step-by-step engineering examples, illustrations, and exercises will be presented. The course will cover a range of machine learning methods for classification, clustering and regression including k-nearest neighbors, logistic regression, Naive Bayes, support vector machines, decision trees, neural networks, support vector machines, genetic programming, and deep learning.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: Letter Grade
Click here for class schedule information.
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