Introduction to Artificial Intelligence
Overview
This unit aims to provide students with an in-depth understanding of algorithmic problem-solving techniques and the sophisticated concepts of artificial intelligence employed to tackle intricate problems. The unit also covers the ethical issues and security risks associated with AI and introduces students to a range of principles and frameworks targeting these issues. It presupposes that students possess proficient programming skills in at least one of the following languages: Python, Java, C#, or C++
Requisites
OR
COS30008 Data Structures and Patterns
Assumed Knowledge
Object oriented programming at an intermediate level
31-May-2026
07-June-2026
07-February-2027
Learning outcomes
Students who successfully complete this unit will be able to:
- Describe and interpret the fundamental concepts of Artificial Intelligence (AI) and generic problem solving techniques
- Identify and explain the ethical principles and frameworks applicable to AI and the security risks associated with AI
- Apply advanced algorithms and data structures to solve complex computing problems
- Design software that implements AI concepts and algorithms in a project-based context
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Live Online Lecture | 2.00 | 8 weeks | 16 |
| On-campus Lecture | 2.00 | 4 weeks | 8 |
| On-campus Class | 2.00 | 12 weeks | 24 |
| Unspecified Activities Independent Learning | 8.50 | 12 weeks | 102 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Major Assignment | Group | 50 - 60% | 1,3,4 |
| Individual Documentation Report | Individual | 15 - 25% | 1,2 |
| Final-Semester Test | Individual | 20 - 35% | 1,3 |
Content
- Introduction to Artificial Intelligence and Intelligent Agents
- Ethics issues and security risks associated with AI systems
- Ethical principles and frameworks applicable to AI systems
- Introduction to Logic and Reasoning
- Uninformed and Informed Search
- Knowledge Representation
- Expert Systems
- AI Planning
- Uncertain Knowledge and Reasoning
- Decision Making with Uncertainty
- Adaptation and Machine Learning
- Philosophical Aspects of AI
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.