Artificial Intelligence for Industry 4.0
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
27-October-2024
02-November-2025
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.