Artificial Intelligence
Master of Electrical EngineeringSpecialisation (formal)Year: 2025
Overview
The proposed Artificial Intelligence specialisation for the Master of Electrical Engineering seeks to address the desire from industry for graduates with a combination of engineering and AI skills and increasing interest from engineering students seeking to integrate Artificial Intelligence into their course of study.
The Artificial Intelligence specialisation is consistent with the other specialisations offered under the Master of Electrical Engineering and consists of a four-subject package:
ELEN90088 System Optimisation and Machine Learning
ELEN90099 Applied Deep Learning for Engineers
ELEN90097 Modelling and Analysis for AI
ELEN90098 Reinforcement Learning for Engineering
These AI-focused subjects will cover relevant concepts and skills that can be applied on top of a sound foundation of electrical engineering knowledge, provided by the first two years of the degree. This instils in students an understanding of AI technologies and trains them to effectively integrate these with engineering principles and practice in order to apply this skill set to the world's challenges.
Intended learning outcomes
On completion of this specialisation, graduates will:
- be able to develop solutions to modern engineering challenges using an engineering systems and advanced computational approach that incorporates multi-disciplinary elements in a fashion that can be analysed, designed, and tested both individually and as a whole;
- be able to apply fundamental knowledge in systems engineering and advanced computational methods for modelling, design, control, and real-world implementation of complex, multi-disciplinary engineering systems;
- be able to analyse and devise solutions for complex, open‐ended real-world engineering problems that demand a combination of engineering domain knowledge and advanced computing (AI/ML) methods;
- be able to execute a data-oriented systems design approach to complex engineering projects, including tasks such as requirements management, system and subsystem integration, prototyping and implementing alternative design solutions, verifying performance against specification, documenting, commissioning and reporting the design outcome.
Last updated: 27 February 2025
Structure
50 credit points
The Artificial Intelligence specialisation is completed by specific subjects (50 credit points embedded within Year 3 requirements).
Note:
1. Students entering the course with advanced standing who plan on completing a specialisation may need to enrol in core specialisation subjects in their commencing semester. Please check and follow the structure outlined for your intended specialisation and seek course planning advice.
2. Students who commenced prior to 2025 can complete their degree following the course structure as per their year of entry/admission. Students in this group can also complete ENGR90051 as part of their Year 1 selective subject options.
To obtain a specialisation in Artificial Intelligence, students must complete:
- 50 credit points of Year 3 core specialisation subjects
Year 1
- 100 credit points of Year 1 compulsory subjects
Year 2
- 100 credit points of Year 2 compulsory subjects
Year 3
- 50 credit points of Year 3 core specialisation subjects
- 25 credit points of Year 3 compulsory capstone project subjects
- 25 credit points of electives
Subject Options
Year 1 compulsory subjects
| Code | Name | Study period | Credit Points |
|---|---|---|---|
| ELEN20005 | Foundations of Electrical Networks |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ELEN20006 | Digital Systems | Semester 1 (On Campus - Parkville) |
12.5 |
| MAST20029 | Engineering Mathematics |
Summer Term (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| COMP20005 | Intro. to Numerical Computation in C |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ELEN30009 | Electrical Network Analysis and Design |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ELEN30011 | Electrical Device Modelling | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN30012 | Signals and Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ELEN30013 | Electronic System Implementation | Semester 2 (On Campus - Parkville) |
12.5 |
Year 2 compulsory subjects
| Code | Name | Study period | Credit Points |
|---|---|---|---|
| ELEN90054 | Probability and Random Models | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90055 | Control Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ELEN90058 | Signal Processing | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90057 | Communication Systems | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90074 | Introduction to Power Engineering | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90056 | Electronic Circuit Design | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90066 | Embedded System Design |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ENGR90051 | Interdisciplinary Design for Engineers |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
(Must be completed in Year 2 of the course)
Year 3 core specialisation subjects
| Code | Name | Study period | Credit Points |
|---|---|---|---|
| ELEN90088 | System Optimisation & Machine Learning | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90099 | Applied Deep Learning for Engineers | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90097 | Modelling and Analysis for AI | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90098 | Reinforcement Learning for Engineering | Semester 2 (On Campus - Parkville) |
12.5 |
(Must be completed in Year 3 of the course)
Year 3 compulsory capstone project subjects
| Code | Name | Study period | Credit Points |
|---|---|---|---|
| ENGR90037 | Engineering Capstone Project Part 1 |
Semester 1 (Extended) (On Campus - Parkville)
Semester 2 (Extended) (On Campus - Parkville)
|
12.5 |
| ENGR90038 | Engineering Capstone Project Part 2 |
Semester 1 (Early-Start) (On Campus - Parkville)
Semester 2 (Early-Start) (On Campus - Parkville)
|
12.5 |
Electrical Engineering Electives (Group A)
| Code | Name | Study period | Credit Points |
|---|---|---|---|
| ELEN90026 | Introduction to Optimisation | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90051 | Advanced Communication Systems | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90052 | Advanced Signal Processing | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90053 | Electronic System Design | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90059 | Lightwave Systems | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90060 | Power System Analysis | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90061 | Communication Networks | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90062 | High Speed Electronics | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90064 | Advanced Control Systems | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90075 | Power Electronics | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90077 | Grid Integration of Renewables | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90088 | System Optimisation & Machine Learning | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90089 | Communication Design Clinic | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90090 | Autonomous Systems Clinic | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90091 | Semiconductor Devices | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90092 | Low-carbon Grids: Operation & Economics | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90093 | Microprocessor Design Clinic | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90094 | Large Data Methods & Applications | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90011 | Directed Studies |
Summer Term (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| ELEN90095 | AI for Robotics | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90096 | Hardware Accelerated Computing | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90083 | Electrical Engineering Research Project |
Summer Term (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
25 |
| ELEN90099 | Applied Deep Learning for Engineers | Semester 2 (On Campus - Parkville) |
12.5 |
| ELEN90097 | Modelling and Analysis for AI | Semester 1 (On Campus - Parkville) |
12.5 |
| ELEN90098 | Reinforcement Learning for Engineering | Semester 2 (On Campus - Parkville) |
12.5 |
Approved Electives (Group B)
| Code | Name | Study period | Credit Points |
|---|---|---|---|
| MAST90014 | Optimisation for Industry | Semester 1 (On Campus - Parkville) |
12.5 |
| COMP90015 | Distributed Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
| MCEN90017 | Advanced Motion Control | Not available in 2025 | 12.5 |
| ENGR90036 | Leadership for Innovation |
Semester 1 (Early-Start) (On Campus - Parkville)
Semester 2 (Early-Start) (On Campus - Parkville)
|
12.5 |
| BUSA90485 | Global Business Practicum |
Summer Term (Off Campus)
July (Off Campus)
November (Off Campus)
|
12.5 |
| ENGR90026 | Engineering Entrepreneurship | Semester 1 (On Campus - Parkville) |
12.5 |
| ENGR90033 | Internship |
Summer Term (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
25 |
| ENGR90046 | Nuclear Engineering | Not available in 2025 | 12.5 |
| ENGR90047 | Radiation Protection | Not available in 2025 | 12.5 |
| ENGR90048 | Engineering of Nuclear Systems | Not available in 2025 | 12.5 |
| ENGR90049 | Nuclear Safety, Security and Safeguards | Not available in 2025 | 12.5 |
| ENGR90034 | Creating Innovative Engineering | Semester 2 (On Campus - Parkville) |
12.5 |
Last updated: 27 February 2025