FIT4009 - Advanced topics in intelligent systems - 2019

6 points, SCA Band 2, 0.125 EFTSL

Undergraduate, Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Information Technology

Chief examiner(s)

Associate Professor Anuja Dharmaratne

Unit guides

Offered

Malaysia

  • Second semester 2019 (On-campus)

Prerequisites

Completion of the Bachelor of Computer Science or equivalent to the entry requirements for the Honours program. Students must also have enrolment approval from the Honours Coordinator.

For students enrolled in E3001, E3002, E3005, E3010, E3011, E3007 completing the Software Engineering specialisation: completion of 144 credit points of study in the Bachelor of Software Engineering (Honours) degree.

Synopsis

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.

Outcomes

On completion of this unit students, should be able to:

  1. describe an overview of different technologies that form the basis of intelligent information systems;
  2. explain the capabilities of these methods;
  3. recognise tasks that can be solved with these methods;
  4. judge the limitations of these methods;
  5. apply several standard techniques in the chosen sub-fields of intelligent information systems to the construction and design of such systems;
  6. critically evaluate the performance of these approaches;
  7. compare these techniques to alternative approaches;
  8. explain the practical relevance of intelligent information systems.

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.

Workload requirements

Minimum total expected workload equals 12 hours per week comprising:

  1. Contact hours for on-campus students:
    • Two hours of lectures
  2. Additional requirements (all students):
    • A minimum of 10 hours independent study per week for completing assignment and project work, private study and revision.

See also Unit timetable information