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INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS

COMPSCI/ECE/ME 539
Course Description

Theory and applications of artificial neural networks: multi-layer perceptron, self-organization mapdeep neural network convolutional neural network, recurrent network, support vector machines genetic algorithm, and evolution computing. Applications to control, pattern recognition, prediction, and object detection and tracking.

Prerequisites

COMPSCI 200 , COMPSCI 220 , COMPSCI 300 , 301, 302, COMPSCI 310 , placement into COMPSCI 300 , or graduate/professional standing

Satisfies
Credits

Not Reported

Offered

Not Reported

Grade Point Average
3.58

11.27% from Historical

Completion Rate
98.88%

3.62% from Historical

A Rate
43.82%

79.87% from Historical

Class Size
89

42.02% from Historical

Cumulative Grade Distribution

Instructors (2026 Summr)

Sorted by ratings from Rate My Professors

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