Graduate Diploma in Computer Science
Course code: GD-CS
March
AUD $45,984 (2026 indicative first year fee). Commonwealth Supported Places (CSPs) are not available
Access Melbourne is available
March
AUD $64,000 (2026 indicative first year fee)
IELTS 6.5: with no band less than 6.0
Course structure
Overview
Students will complete between four and six core subjects, with the electives making up a total of eight subjects.
Visit the Handbook for more information:
Explore this course
Explore the subjects you could choose as part of this diploma.
Students must complete all of the following subjects:
| Accordion | |
|---|---|
| Internet Technologies · 12.5 pts |
AIMS The subject will introduce the basics of computer networks to students through a study of layered models of computer networks and applications. The first half of the subject deals with data communication protocols in the lower layers of OSI and TCP/IP reference models. The students will be exposed to the working of various fundamental networking technologies such as wireless, LAN, RFID and sensor networks. The second half of the subject deals with the upper layers of the TCP/IP reference model through a study of several Internet applications. INDICATIVE CONTENT Topics covered include: Introduction to Internet, OSI reference model layers, protocols and services, data transmission basics, interface standards, network topologies, data link protocols, message routing, LANs, WANs, TCP/IP suite, detailed study of common network applications (e.g., email, news, FTP, Web), network management, and current and future developments in network hardware and protocols. |
| Algorithms and Complexity · 12.5 pts |
AIMS The aim of this subject is for students to develop familiarity and competence in assessing and designing computer programs for computational efficiency. Although computers manipulate data very quickly, to solve large-scale problems, we must design strategies so that the calculations combine effectively. Over the latter half of the 20th century, an elegant theory of computational efficiency developed. This subject introduces students to the fundamentals of this theory and to many of the classical algorithms and data structures that solve key computational questions. These questions include distance computations in networks, searching items in large collections, and sorting them in order. INDICATIVE CONTENT Topics covered include complexity classes and asymptotic notation; empirical analysis of algorithms; abstract data types including queues, trees, priority queues and graphs; algorithmic techniques including brute force, divide-and-conquer, dynamic programming and greedy approaches; space and time trade-offs; and the theoretical limits of algorithm power. |
| Programming and Software Development · 12.5 pts |
AIMS The aim for this subject is for students to develop an understanding of approaches to solving moderately complex problems with computers, and to be able to demonstrate proficiency in designing and writing programs. The programming language used is Java. INDICATIVE CONTENT Topics covered will include:
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And
One of the following subjects:
| Accordion | |
|---|---|
| Database Systems · 12.5 pts |
AIMS Contemporary online services such as social networking and multimedia-sharing sites, massive multiplayer online games and commerce services have database management systems at their back-end. In this subject, students will obtain a deep understanding of the concepts behind database management systems. In particular, the students will become familiar with the database system architecture, and will exercise the concepts such as query processing and optimisation, database tuning and transactions, which are the foundation of any modern data processing application. This subject is core within the Bachelor of Science for the Major of Computing and Software Systems and the Major of Informatics. Students completing the Diploma of Informatics are also required to undertake this subject. INDICATIVE CONTENT This subject serves as an introduction to data modelling and databases from a technical and data management perspective. The subject will include Entity Relationship modelling (from conceptual design to physical modelling), normalisation, de-normalisation, relational model and relational algebra, SQL, query processing and query optimisation, transactions, storage organisation, database administration, data warehousing and big data analytics. Other topics in data management and DBMS technology with an overview of modern NoSQL systems may also be included. |
| Elements of Data Processing · 12.5 pts |
AIMS Data processing is fundamental to computing and data science. This subject covers various aspects of data processing including database management, representation and analysis of data, information retrieval, visualisation and reporting, and cloud computing. This subject includes an emphasis on both tools and underlying foundations. INDICATIVE CONTENT The subject's focus is on the data pipeline, and activities known colloquially as 'data wrangling'. Indicative topics covered include:
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Remaining points to be made up from:
| Accordion | |
|---|---|
| Artificial Intelligence · 12.5 pts |
AIMS Artificial intelligence is the quest to create intelligent agents that can complete complex tasks which are at present only achievable by humans. This broad field covers logic, probability, perception, reasoning, learning and action; and everything from Mars Rover robotic explorers to the Watson Jeopardy playing program. You will explore some of the vast area of artificial intelligence. Topics covered include: searching, problem solving, reasoning, knowledge representation and machine learning. Topics may also include some of the following: game playing, expert systems, pattern recognition, machine vision, natural language, robotics and agent-based systems. INDICATIVE CONTENT
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| Declarative Programming · 12.5 pts |
AIMS Declarative programming languages provide elegant and powerful programming paradigms which every programmer should know. This subject presents declarative programming languages and techniques. INDICATIVE CONTENT
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| Graphics and Interaction · 12.5 pts |
AIMS This subject introduces technologies and theoretical foundations of computer graphics and human-computer interaction (HCI) along with the aspects of human perception and action that inform their applications. The subject emphasises the 2D and 3D computer graphics pipeline, from the geometric modelling to visual representation and interaction with virtual environments. Core topics include geometry representation, 3D transformations, illumination models, rendering algorithms, animation, and object interactions. These technologies form the basis for developing 3D game engines and interactive applications across platforms ranging from PCs to tablet computers, incorporating natural user interfaces (NUIs). Applications explore computer games, virtual and augmented reality, movie visual effects, and social applications such as metaverse. The subject also extends into immersive multimodal interaction. This subject supports course-level objectives by allowing students to develop analytical and technical skills essential for developing and implementing real-world solutions in computer graphics and interaction applications. INDICATIVE CONTENT Topics are drawn from computer graphics and human-computer interaction including:
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| IT Project · 12.5 pts |
AIMS This subject is the capstone project for the Informatics major and the Computing and Software Systems major in the BSc. Students will work on a real life problem in a small team, supervised by a member of staff. Each team will analyse the information needs of users and develop working computational solutions. Students are expected to apply sound principles studied over the course of their degree to the formulation and solution of their problem. INDICATIVE CONTENT Students will work in teams to analyse, design, implement and test a non-trivial IT system. A key part of the project is for students to develop and manage a project in order to deliver a quality IT product. Workshops will explore the application of theory to the project and include selected topics drawn from: ethics, project management, design frameworks, testing, technical reviews, and product evaluation. |
| Models of Computation · 12.5 pts |
AIMS Formal logic and discrete mathematics provide the theoretical foundations for computer science. This subject uses logic and discrete mathematics to model the science of computing. It provides a grounding in the theories of logic, sets, relations, functions, automata, formal languages, and computability, providing concepts that underpin virtually all the practical tools contributed by the discipline, for automated storage, retrieval, manipulation and communication of data.
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| Declarative Programming · 12.5 pts |
AIMS Declarative programming languages provide elegant and powerful programming paradigms and techniques that every programmer should know. This subject presents declarative programming languages and techniques. INDICATIVE CONTENT
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| Software Modelling and Design · 12.5 pts |
AIMS To construct a software system, requirements must be analysed and modelled, and designs developed and evaluated; this subject teaches knowledge and skills needed for these tasks. This includes the development of static and dynamic models for aspects of both the problem space and the solution space. The emphasis here is on an Agile approach, and on techniques appropriate for object-oriented development. INDICATIVE CONTENT Topics covered include:
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| Distributed Systems · 12.5 pts |
AIMS The subject aims to provide an understanding of the principles on which the Web, Email, DNS and other interesting distributed systems are based. Questions concerning distributed architecture, concepts and design; and how these meet the demands of contemporary distributed applications will be addressed. INDICATIVE CONTENT Topics covered include: characterization of distributed systems, system models, interprocess communication, remote invocation, indirect communication, operating system support, distributed objects and components, web services, security, distributed file systems, and name services. |
| Introduction to Machine Learning · 12.5 pts |
AIMS Machine Learning is the study of making accurate, computationally efficient, interpretable and robust inferences from data, often drawing on principles from statistics. This subject aims to introduce students to the intellectual foundations of machine learning, including the mathematical principles of learning from data, algorithms and data structures for machine learning, and practical skills of data analysis. INDICATIVE CONTENT Indicative content includes: cleaning and normalising data, supervised learning (classification, regression, linear & non-linear models), and unsupervised learning (clustering), and mathematical foundations for a career in machine learning. |
| The Ethics of Artificial Intelligence · 12.5 pts |
This subject aims to provide students with the necessary tools to: identify social and ethical issues of digital technology particularly artificial intelligence and reason about these issues; communicate concerns, or discuss ideas, from differing points of view; and ultimately build technology with awareness of, and respect for, inclusion and the responsibility that comes with building powerful tools. Not contemplating ethical or social implications of AI and other technological tools may open up unintended consequences and risks. Ethical dilemmas can also cause additional personal stress for individuals who lack the skills to think about them reflectively. For these reasons, the growing societal and ethical problems raised by artificial intelligence and other technologies have become a major focus of many organisations, including for start-ups, government, defence, and many corporations. Topics include:
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