Availabilities:

Not currently available in 2018

Unit Summary

Unit type

PG Coursework Unit

Credit points

12

AQF level

9

Level of learning

Advanced

Pre-requisites

- Big Data Analysis and Tools

Unit aim

Focuses on real-world applications of intelligent systems. Students undertake a series of selected case studies on state-of-the-art applications of artificial intelligence. The students will evaluate, critique, reflect-on and improve the case studies. This unit provides the students with understanding of contemporary artificial intelligence practices for real-world problem solving.

Unit content

1. Introduction to applications and practices of developing advanced intelligent systems

2. Methodology to critique existing approaches, techniques and solutions

3. Case studies of advanced AI techniques

4. Research-driven improvements of advanced AI techniques

5. Future trends of intelligent systems

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

GA1: , GA2: , GA3: , GA4: , GA5: , GA6: , GA7:
On completion of this unit, students should be able to: GA1 GA2 GA3 GA4 GA5 GA6 GA7
1 identify and evaluate state-of-the-art systems and applications of current practices in utilising artificial intelligence for assisting expert decision making.
2 reflect on and critique contemporary applications of artificial intelligence techniques in a variety of contexts
3 design and develop enhancements to existing artificial intelligence solutions for real-world problems
4 critically analyse future trends and developments in intelligent systems and applications

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

  1. identify and evaluate state-of-the-art systems and applications of current practices in utilising artificial intelligence for assisting expert decision making.
    • GA4:
  2. reflect on and critique contemporary applications of artificial intelligence techniques in a variety of contexts
    • GA2:
    • GA4:
  3. design and develop enhancements to existing artificial intelligence solutions for real-world problems
    • GA2:
  4. critically analyse future trends and developments in intelligent systems and applications
    • GA4:
    • GA5: