Artificial Intelligence for Industry 4.0
88 Hours
One Semester or equivalent
Hawthorn
Overview
The purpose of this unit is to introduce students to the industrial applications of artificial intelligence, with a focus on machine learning. Students will gain an understanding of the business, societal and industrial benefits of AI. They will learn techniques to model and manage data using contemporary technologies and apply statistical techniques to evaluate the output.
Requisites
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 2
Location
Hawthorn
Start and end dates
03-August-2026
01-November-2026
01-November-2026
Last self-enrolment date
16-August-2026
Census date
01-September-2026
Last withdraw without fail date
22-September-2026
Results released date
08-December-2026
Semester 2
Location
Hawthorn
Start and end dates
03-August-2026
01-November-2026
01-November-2026
Last self-enrolment date
16-August-2026
Census date
01-September-2026
Last withdraw without fail date
22-September-2026
Results released date
08-December-2026
Semester 2
Location
Hawthorn
Start and end dates
02-August-2027
31-October-2027
31-October-2027
Last self-enrolment date
15-August-2027
Census date
31-August-2027
Last withdraw without fail date
21-September-2027
Results released date
07-December-2027
Semester 2
Location
Hawthorn
Start and end dates
02-August-2027
31-October-2027
31-October-2027
Last self-enrolment date
15-August-2027
Census date
31-August-2027
Last withdraw without fail date
21-September-2027
Results released date
07-December-2027
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Demonstrate an understanding of problem-solving using programming skills.
- Demonstrate an understanding of artificial intelligence concepts and the practical applications
- Apply basic principles, models and algorithms in artificial intelligence to solve problems in Industry 4.0 contexts
- Identify real-world problems and select the most appropriate artificial intelligence method to solve the problem
- Examine ethical issues which arise when artificial intelligence is applied.
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Face to Face Contact (Phasing out) Laboratory | 4.00 | 11 weeks | 44 |
| Face to Face Contact (Phasing out) Laboratory | 4.00 | 11 weeks | 44 |
| Placement Placement | 8.00 | 1 week | 8 |
| Online Directed Online Learning and Independent Learning | 4.00 | 1 week | 4 |
| Unspecified Learning Activities (Phasing out) Individual Study | 50.00 | 1 week | 50 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Assignment | Individual | 20 - 30% | 1,2,3 |
| Presentation | Group | 10 - 20% | 1,2,3,4,5 |
| Project | Group | 10 - 20% | 1,2,3,4,5 |
| Test 1 | Individual | 10 - 20% | 3,4 |
Content
- Introduction to Programming Principles (e.g. Python,XML, SQL, R)
- Introduction to Machine Learning and AI
- Supervised & Unsupervised Learning
- Regression analysis
- Probability and Statistics
- AI/ML Development Tools Analytics
- Applications of AI in Advanced Manufacturing
- Benefits and Risks of AI implementation
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.