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Artificial Intelligence
Master of Digital Infrastructure EngineeringSpecialisation (formal)Year: 2024
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 Specialisation compulsory subjects
- 12.5 credit points of Specialisation selectives
Subject options
Specialisation compulsory subjects
Code | Name | Study period | Credit Points |
---|---|---|---|
COMP90038 | Algorithms and Complexity |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90049 | Introduction to Machine Learning |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90051 | Statistical Machine Learning |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Specialisation selectives
Code | Name | Study period | Credit Points |
---|---|---|---|
COMP90054 | AI Planning for Autonomy |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90086 | Computer Vision | Semester 2 (On Campus - Parkville) |
12.5 |
Last updated: 3 May 2024