FIT4009 Advanced Topics in Intelligent Systems

Methods from Artificial Intelligence (AI) form the basis for many advanced information systems. These techniques address problems that are difficult to solve or not efficiently solvable with conventional techniques. Building on the undergraduate curriculum this unit introduces the student to advanced AI methods and their applications in information systems.

Topics for this unit include:

Machine Learning
Data Mining and Knowledge Discovery
Artificial Life
Automated Reasoning
Knowledge-based Systems Search
Constraint Solving and Optimization
Natural Language Processing
Computer Vision and Pattern Recognition

Teaching

Lectures, supervised study of research literature, and independent computational experiments with feedback from lecturers. Where appropriate students will learn to use work with software packages that represent the state-of-the-are in the research field.

Assessment

Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.

Prerequisites

Completion of an approved bachelor degree in computer science, or equivalent to the entry requirements for the Honours program. Students must also have enrolment approval from the Honours Coordinator.

Corequisites

None.

Prohibitions

None.