BUS3650

Business applications of neural networks

(IT)

K Smith

6 points + One 2 hour lecture and one 1-hour tutorial per week + First and summer semester, Clayton

Synopsis: This course provides students with the skills necessary to solve practical business problems using commercially available neural network software. The focus is on the business application, with suitable neural network architectures and training issues discussed with reference to each particular application. Topics to be covered include principles and mechanisms in neural networks; perceptrons for marketing, and business data classification/analysis; multilayer feedforward neural networks for time series and stock market prediction, and written character recognition; convergence issues of neural networks, data mining methodologies, and artificial intelligence in business.

Assessment: Examination (2 hours): 50% + Practical work (assignments): 30% + Mid-semester test: 20% + Students must pass the examination in order to pass the subject.