Introduction to Artificial Intelligence
32 hours face to face + blended
Hawthorn, Online
Available to incoming Study Abroad and Exchange students
Overview
This unit is designed to give students a broad outline of algorithmic problem solving and the basic concepts of artificial intelligence. It is assumed that students already have good programming skills in at least one of the programming languages Java/C/C++.
Requisites
Prerequisites
COS20007
Object Oriented ProgrammingOR
COS30008 Data Structures and Patterns
Assumed Knowledge
Object oriented programming at an intermediate level
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Teaching Period 3
Location
Online
Start and end dates
04-November-2024
09-February-2025
09-February-2025
Last self-enrolment date
17-November-2024
Census date
29-November-2024
Last withdraw without fail date
27-December-2024
Results released date
04-March-2025
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
- Apply advanced algorithms and data structures to solve common problems
- Design software that implements AI concepts
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 |
All Applicable Locations
Type | Hours per week | Number of weeks | Total (number of hours) |
---|---|---|---|
Online Directed Online Learning and Independent Learning | 12.50 | 12 weeks | 150 |
TOTAL | 150 |
Assessment
Type | Task | Weighting | ULO's |
---|---|---|---|
Assignment 1 | Individual | 20 - 30% | 2,3 |
Assignment 2 | Group | 20 - 30% | 2,3 |
Final-Semester Test | Individual | 20 - 30% | 1,2 |
Mid-Semester Test | Individual | 20 - 30% | 1,2 |
Content
- Introduction to Artificial Intelligence and Intelligent Agents
- 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.