Diploma
Graduate Diploma in Computer Science
- CRICOS Code: 099421E
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What will I study?
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.
List A
Students must choose at least two of:
- Elements of Data Processing 12.5 pts
AIMS
Data processing is fundamental to computing and data science. This subject gives an introduction to various aspects of data processing including database management, representation and analysis of data, information retrieval, visualisation and reporting, and cloud computing. This subject introduces students to the area, with 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:
- Capturing data (data ingress)
- Data representation and storage
- Cleaning, normalisation and filling in missing data (imputation)
- Combing multiple sources of data (data integration)
- Query languages and processing
- Scripting to support the data pipeline
- Distributing a database over multiple nodes (sharding), cloud computing file systems
- Visualisation and presentation
- Introduction to Programming 12.5 pts
AIMS
This subject introduces the fundamental concepts of computing programming, and how to solve simple problems using high-level procedural language, with a specific emphasis on data manipulation, transformation, and visualisation of data.
INDICATIVE CONTENT
Fundamental programming constructs; fundamental data structures; abstraction; basic program structures; algorithmic problem solving; use of modules.
The subject assumes no prior knowledge of computer programming.
- 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.
List B
Students must choose at least two of:
- 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 aims 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:
- Java basics
- Console input/output
- Control flow
- Defining classes
- Using object references
- Programming with arrays
- Inheritance
- Polymorphism and abstract classes
- Exception handling
- UML basics
- Interfaces
- Generics
- 12.5 ptsGraphics and Interaction
AIMS
This subject introduces the technologies of computer graphics and human-computer interaction along with the biological, psychological and social aspects of human perception and action that inform the application of those technologies. The emphasis is on 2D and 3D computer graphics and the geometric modelling techniques used for representing and interacting with objects in dynamic scenes. Techniques considered include transformation geometry, illumination models and the real-time rendering (shading) models. The subject is centred on developing Apps for tablet computers based on natural user interfaces (NUIs), a term used by developers of human-machine interfaces that effectively become invisible to their users through successive learned interactions. Technologies likely to be considered are: virtual reality, computer games, augmented reality, tele-presence, or other modalities such as interaction through the sense of touch, audio or image processing and analysis. This subject supports course-level objectives by allowing students to develop analytical skills to understand the complexity of developing real-world computer graphics and interaction applications.
INDICATIVE CONTENT
Topics are drawn from computational geometry and human-computer interaction including:
- 2D and 3D computer graphics
- Colour and illumination models
- Raster and vector graphics
- Geometric modelling
- Rendering (shading) and visualisation
- Geometric transformations (including projection)
- Computational matrix geometry and/or animation (kinematics)
- Interaction categories and styles (particularly graphical user interfaces)
- Usability and accessibility (including interaction for people with disabilities).
- 12.5 ptsDeclarative Programming
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
- The dangers of destructive update
- Functional programming
- Recursion
- Strong type systems
- Parametric polymorphism
- Algebraic types
- Type classes
- Defensive programming practice
- Higher order programming
- Currying and partial application
- Lazy evaluation
- Monads
- Logic programming
- Unification and resolution
- Nondeterminism, search, and backtracking.
- 12.5 ptsIT Project
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.
- 12.5 ptsArtificial Intelligence
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
- Agents and search
- Probabilistic reasoning
- Reinforcement Learning
- Pattern recognition for robotics.
- 12.5 ptsModels of Computation
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.
INDICATIVE CONTENT
- Logic: Propositional and predicate logic, resolution proofs, mathematical proof
- Discrete mathematics: Sets, functions, relations, order, well-foundedness, induction and recursion
- Automata: Regular languages, finite-state automata, context-free grammars and languages, parsing
- Computability briefly: Turing machines, computability, decidability
A functional programming language will be used to implement and illustrate concepts.
- 12.5 ptsMachine Learning
AIMS
Machine Learning, a core discipline in data science, is prevalent across Science, Technology, the Social Sciences, and Medicine; it drives many of the products we use daily such as banner ad selection, email spam filtering, and social media newsfeeds. Machine Learning is concerned with making accurate, computationally efficient, interpretable and robust inferences from data. Originally borne out of Artificial Intelligence, Machine Learning has historically been the first to explore more complex prediction models and to emphasise computation, while in the past two decades Machine Learning has grown closer to Statistics gaining firm theoretical footing.
This subject aims to introduce undergraduate students to the intellectual foundations of machine learning, and to introduce practical skills in data analysis that can be applied in graduates' professional careers.
CONTENT
Topics will be selected from: prediction approaches for classification/regression such as k-nearest neighbour, naïve Bayes, discriminative linear models, decision trees, Support Vector Machines, Neural Networks; clustering methods such as k-means, hierarchical clustering; probabilistic approaches; exposure to large-scale learning.
- 12.5 ptsDistributed Systems
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.
- 12.5 ptsDeclarative Programming
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
- The dangers of destructive update
- Functional programming
- Recursion
- Strong type systems
- Parametric polymorphism
- Algebraic types
- Type classes
- Defensive programming practice
- Higher order programming
- Currying and partial application
- Lazy evaluation
- Monads
- Logic programming
- Unification and resolution
- Nondeterminism, search, and backtracking
- 12.5 ptsIntroduction to Machine Learning
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.
- 12.5 ptsWeb Information Technologies
AIMS
The Web has radically changed society, politics, science, business and the way people work. This subject introduces the concepts, technologies and standards underpinning the World Wide web and its applications. You will learn to apply tools and techniques required to model, design and develop applications for the web that can run on one or more platforms. Topics covered include the infrastructure of the web; the architecture of web applications; data representation and structure of the web; modeling and development processes for Web applications; security and social aspects of the Web. This subject assumes background programming skills and the basics of algorithmic thinking. These skills are combined with incremental and iterative development to develop functional and creative web applications that can support specific requirements or aspects of human work or social behaviour.
INDICATIVE CONTENT
Fundamental aspects of the Web: client server model, modelling of web applications (modelling data, content, functional aspects and navigation), incremental and iterative design and development of web applications, usability aspects and testing of web applications, and web application security.
Examples of Web applications that students develop are:
- A location-aware application for finding recommended restaurants nearby
- A social app for hosting and developing HTML5 games
- An application that lets users upload photos of themselves to see what they’d look like with different hairstyles
- 12.5 ptsSoftware Modelling and Design
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:
- Analysis and modelling requirements
- Developing, modelling and evaluating designs
- Modelling using the Unified Modelling Language (UML)
- Software design processes and principles
- Common design patterns and software architectures
- Tools for design and development