Artificial Intelligence
Master of Digital Infrastructure EngineeringSpecialisation (formal)Year: 2023
You’re currently viewing the 2023 version of this component
Artificial Intelligence
Overview
Intended learning outcomes
On completion of this course, graduates of the Master of Digital Infrastructure Engineering will have:
- A body of knowledge that includes the understanding of recent developments in spatial engineering fundamentals and practice;
- Knowledge of research principles and methods applicable to a field of work or learning;
- Cognitive skills to demonstrate mastery of theoretical knowledge and to reflect critically on theory and professional practice or scholarship;
- Cognitive, technical and creative skills to investigate, analyse and synthesise complex information, problems, concepts and theories and to apply established theories to different bodies of knowledge or practice;
- Cognitive, technical and creative skills to generate and evaluate complex ideas concepts at an abstract level;
- Communication and technical research skills to justify and interpret theoretical propositions, methodologies, conclusions and professional decisions to specialist and non-specialist audiences;
- Technical and communication skills to design, evaluate, implement, analyse, theorise about developments that contribute to professional practice or scholarship;
- Gained creativity and initiative to new situations in professional practice and/or for further learning;
- High level personal autonomy and accountability;
- The skills to plan and execute a substantial research-based project, capstone experience and/or piece of scholarship.
Last updated: 3 May 2024
Structure
50 credit points
The Artificial Intelligence specialisation is completed by undertaking:
- 37.5 credit points of Year 3 specialisation compulsory subjects
- 12.5 credit points of Year 3 specialisation selectives
Subject options
Year 3 specialisation compulsory subjects
Code | Name | Study period | Credit Points |
---|---|---|---|
COMP90038 | Algorithms and Complexity |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90049 | Introduction to Machine Learning |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90051 | Statistical Machine Learning |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Year 3 specialisation selectives
Code | Name | Study period | Credit Points |
---|---|---|---|
COMP90054 | AI Planning for Autonomy |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90086 | Computer Vision | Semester 2 (On Campus - Parkville) |
12.5 |
Last updated: 3 May 2024