FIT5186 - Intelligent systems - 2019

This unit introduces main techniques widely used in intelligent software systems to students in the Master of Information Technology Systems course with the Network Computing major. Specifically, it focuses on the techniques in relation to network structures. Main topics covered include neural network models, supervised learning and classification, unsupervised learning and clustering, fuzzy logic, intelligent decision analysis, optimum network flow modelling, and recommender systems.

On completion of this unit, students will have a knowledge and understanding of:

1. Explain the principles and theoretical underpinning of intelligent systems
2. Develop intelligent models and conduct experiments for solving a specific problem
3. Describe and evaluate the advantages and limitations of intelligent models and techniques for solving a wide range of practical problems
4. Analyse and evaluate current research developments in intelligent systems

Examination (2 hours): 60%; In-semester assessment: 40%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hours of lectures
   • One 2-hour laboratory
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information