Intelligent Systems
Duration
- One Semester or equivalent
Contact hours
- 36 hours face to face + blended
On-campus unit delivery combines face-to-face and digital learning.
2023 teaching periods
| Hawthorn Higher Ed. Semester 2 |
||
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
COS20007 Object-Oriented Programmingor
or
or
Assumed knowledge:
Object oriented programming at an intermediate level
Aims and objectives
This unit is designed to introduce students to a range of artificial intelligence techniques.
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Explain a range of techniques of intelligent systems across artificial intelligence (AI) and intelligent agents (IA); both from a theoretical and a practical perspective.
2. Apply different AI/IA algorithms to solve practical problems.
3. Design and build intelligent systems based on AI/IA concepts.
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
On Campus Lecture | 2 | 4 | 8 |
| Live Online Lecture | 2 | 8 | 16 |
| On Campus Class in Computer Lab | 2 | 12 | 24 |
Unspecified Activities Independent Learning | 8.5 | 12 | 102 |
TOTAL | 150 hours |
Assessment
| Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
| Examination | Individual | 50% | 1,2 |
| Project | Group | 50% | 1,2,3 |
Minimum requirements to pass this unit
As the minimum requirements of assessment to pass the unit and meet all Unit Learning Outcomes to a minimum standard, a student must achieve:
As the minimum requirements of assessment to pass the unit and meet all Unit Learning Outcomes to a minimum standard, a student must achieve:
(i) An aggregate mark of 50% or more, and
(ii) At least 40% in the final exam
Students who do not successfully achieve hurdle requirement (ii) will receive a maximum of 44% as the total mark for the unit and will not be eligible for a conceded pass.
Content
- Introduction to Intelligent Systems
- Knowledge representation and reasoning
- Intelligent agents and multi-agent systems
- Learning and adaptation
- Evolutionary computing
- Neural networks
- Collective intelligence
- Methodologies and applications
Study resources
- Reading materials.
Reading materials
A list of reading materials and/or required texts will be made available in the Unit Outline.