Neural networks are an emerging technology gaining wide acceptance in the business community. Many corporations are currently using neural networks for a variety of business applications including finance and investment, marketing, data mining and project management. The popularity of neural networks is expected to continue to increase, as businesses become more informed about the power of neural networks. Many of our Sponsor organisations such as IBM are very active in intelligent techniques, and are keen to recruit graduates with knowledge of these emerging technologies. A variety of commercial software is available for neural networks, and graduates of Business Information Systems degrees should be aware of how this technology can be a useful solution tool in a business environment.

The code for this unit has been changed from BUS5650 to FIT5070 in accordance with new Faculty procedures.

This unit is an elective unit in the Master of Business Systems.

This unit is a recoding of BUS5650.

This unit helps students develop practical business problem solving abilities using neural network techniques.

ASCED Discipline Group classification: 020119 Artificial Intelligence

Neural networks have been receiving increasing attention from business and industry over recent years. This course will provide students with the skills necessary to solve practical business problems using commercially available neural network software. The focus of the course will be on the business application, with suitable neural network architectures and convergence issues discussed with reference to each particular application. Students will gain hands-on experience with commercial neural network software packages, and will solve real business problems in tutorials and assignments. Topics to be covered include principles and mechanisms in neural networks; Perceptrons for marketing, and business data classificationanalysis; 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.

This course will provide students with the skills necessary to solve practical business problems using commercial neural network software. The focus of the course will be on the business application, with suitable neural network models discussed with reference to each particular application. Students will gain hands-on experience with commercial software packages in tutorials and assignments. 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, data mining methodologies, and artificial intelligence in business.

1 full-time lecturer and 2 part-time (sessional) tutors

100% from Clayton School of Information Technology

No

Nil

Chung-Hsing Yeh