Monash home | About Monash | Faculties | Campuses | Contact Monash |
Staff directory | A-Z index | Site map |
Postgraduate |
(IT)
|
Leader:
Offered:
Clayton Second semester 2006 (Day)
Synopsis: Solving practical business problems using commercially available neural network software. Focuses on business applications, with discussion of suitable neural network architectures and convergence issues. Students gain hands-on experience with commercial neural network software packages, and solve real business problems in labs and assignments. Topics include principles and mechanisms in neural networks; perceptions for marketing and business data classification/analysis; multilayer feedforward neural networks for time series, 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 (assignment): 30% + Mid-semester test: 20% + Students must pass the examination in order to pass the unit
Contact Hours: One x 2hour lecture/week, one x 1hour laboratory/week
Prerequisites: BUS9530 or equivalent quantitative unit
Prohibitions: BUS3650, BUS4650