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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.

Prerequisties

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

Satisfies
Credits

3

Offered

Fall

Grade Point Average
3.32

4.15% from Historical

Completion Rate
96.43%

1.43% from Historical

A Rate
29.76%

33.3% from Historical

Class Size
84

38.19% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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