Develop expertise in the fundamental principles of machine and deep learning underpinning modern Artificial Intelligence (AI), complement your engineering knowledge with advanced computational skills, and learn how to use AI methods effectively in electrical engineering application domains.
Why AI Specialisation*
The AI specialisation for electrical engineering students is a forward-looking pathway that unites the rigour of engineering with the power of artificial intelligence. While AI alone enables data-driven insights and automation, its true potential is unlocked when paired with a deep understanding of physical systems, hardware constraints, and real-world infrastructure, the core strengths of engineering. This specialisation equips students with both the analytical skills to build intelligent algorithms and the engineering expertise to apply them effectively in complex environments. As industries accelerate their adoption of smart technologies, there is a growing demand for professionals who can bridge the gap between abstract AI models and tangible engineering applications. Graduates will be uniquely positioned to design intelligent, efficient, and sustainable systems across sectors such as energy, telecommunications, manufacturing, and advanced technology. By integrating AI into their electrical engineering foundation, students gain a powerful advantage, enabling innovation not just in code but in the systems that shape our world.
* This blurb was provided by AI and then edited using an iterative process!
Teaching team
The future belongs to engineers who master both the physical and digital realms. We need professionals who don’t just build systems but optimise them—using Artificial Intelligence not as a buzzword, but as a tool for real-world impact. When electrical engineering meets machine learning, and when systems thinking is paired with prescriptive models like optimisation algorithms and nonlinear programming, we unlock the potential to design the intelligent, efficient, and sustainable infrastructures of tomorrow. Dayeli Manuet, AI & Analytics Leader
Structure
The program shown in the table above is built up of the following parts:
- Sixteen foundational subjects that are core to all specialisations of the degree. The foundational subjects are the eight subjects taken in Year 1 and Year 2 which together provide you with a solid foundation from which to specialise.
- Four core subjects that are bespoke to achieving the chosen specialisation. These subjects build upon the foundations of electrical engineering.
- An individualised capstone project that is an outlet for all the expertise you have developed.
- A subject that focuses on professional skills development.
- Two elective subjects to explore your interests and develop expertise across any of our specialisation areas.
Core subjects
The 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. 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 to apply this skill set to the world's challenges.
The following subjects are designed and taught in an integrated manner, resulting in a coherent study package. All of these core subjects are taught in a project-oriented way, seamlessly integrating practical, hands-on learning with theoretical knowledge.
- In ELEN90097, students learn how to simulate engineering models, store and organise the resulting data along with fundamentals of data structures, databases, algorithms, and logic.
- In ELEN90088, students learn fundamentals of convex optimisations and machine learning basics such as model selection, training, and bounds, as well as neural networks and backpropagation.
- In ELEN90099, students learn deep learning principles and widely used architectures such as transformers and generative models, and how to apply them to electrical engineering problems.
- In ELEN90098, students learn theoretical foundations of reinforcement learning, such as dynamic programming and Markov decision processes, as well as modern deep reinforcement learning and their electrical engineering applications.
Capstone project
Core to all specialisations is the year-long capstone project that is completed in teams of 3 or 4. Through the capstone project you and your team develop solutions to an unsolved problem. The project is tailored to your interests, ranging from: research and development projects proposed by our world-class academics; to multi-team projects that partake in international and local competitions; to innovative projects proposed by you. See the handbook entry for further details.
Professional skills subject
To develop and strengthen the skills necessary to operate as a professional engineer upon graduation, you will take the following subject:
Interdisciplinary Design for Engineers (ENGR90051)
In this subject, students will actively engage in an interdisciplinary, collaborative and project-based learning environment, offering insights into the professional nature of engineering work. Through a real-world project, students will gain hands-on design experience addressing a complex challenge. The project will require students to integrate discipline knowledge and apply professional skills like teamwork and communication.
Elective subjects
To obtain the degree with a specialisation, students must also complete 25 credit points of Electrical Engineering Elective (Group A) subjects (Business specialisation only) or 25 credit points of Electrical Engineering (Group A) or Approved Elective (Group B) subjects (for other specialisations other than Business).
A full list of Electives (Group A) and Approved Electives (Group B) can be found in the handbook entry for the Master of Electrical Engineering.
Master of Electrical Engineering handbook