Graduate Diploma of Cybersecurity

In Network Design and Security, students will be introduced to principles of network communications, topologies, and security protocols. Contemporary and advanced techniques for managing and protecting computing networks will be explored to ensure the protection of commercially processed data and their supported applications. Students will be given an opportunity to design and evaluate a contemporary computing network with a focus on next generation firewalls, access management systems and attack resilience for secure enterprises.

Assessment Tasks: Online test, report, presentation

Delivery Mode: On Campus, Online

Are there many applications in business that don’t require programming? This subject explores programming and equips you with the skills to create applications that address business requirements. Throughout the subject, you will gain proficiency in using a graphical representation technique, i.e., flowchart, which will enable you to design, analyse, and optimise software solutions.

Furthermore, you will learn how to use an Integrated Development Environment (IDE) to create, test, and run programs while applying object-oriented concepts to effectively solve organizational problems. By the end of the subject, you will understand the object-oriented paradigm, allowing you to assess and apply business requirements in real-world scenarios.

Assessment Tasks: Coding essentials, report

Delivery Mode: On Campus, Online

Software Fortress and Web protection introduces students to the tools and methodologies to secure software and web applications against external threats and internal risks. Important topics will be explored, such as advanced risk management in software systems, development of resilient systems to safeguard data and applications, and sustained protection of users and data against emerging cybersecurity attacks. Upon completion of this subject, the students have the skills and knowledge needed to develop sustainable and dependable software and web systems according to the industry standards.

Pre-requisite: MIS501 Principles of Programming

Assessment Tasks: Report, presentation

Delivery Mode: On Campus, Online

This subject will introduce students to the methodologies and techniques that enable secure digital infrastructure, including the Internet of Things (IoT), cloud networks and extended computing networks. Students will investigate specialist topics relevant to contemporary and future industries, such as Artificial Intelligence (AI) driven security solutions, IoT infrastructure, and cloud-enabled secure environments. The knowledge and skills acquired in the subject will equip students with the ability to devise innovative cybersecurity solutions to protect digital infrastructure for public safety and a sustainable future society.

Pre-requisite: NDS441 Network Design and Security

Assessment Tasks: Report, Presentation

Delivery Mode: On Campus, Online

Research and development (R&D) in the Information Communication Technology (ICT) sector is critical for an organisation’s growth and sustainability. Identifying ICT related challenges and producing timely, informed solutions ensures an organisation’s competitive advantage in the industry. This subject introduces students to the life cycle of the R&D process. This starts with problem formulation through critical thinking approaches and competition analysis through literature review and market analysis. Students will evaluate and propose research-informed, innovative ICT solutions with quantitative and qualitative analysis. This will be followed by communication of the solutions to the relevant stakeholders for appraisal and agile development. Ethical principles will also be examined and applied to the design of R&D solutions. On successful completion of this subject, students will be able to lead projects in research-informed ICT innovations and contribute to both professional and academic communities.

Assessment Tasks: Report, presentation

Delivery Mode: On Campus, Online

This subject is designed to provide a graduate-level student an in-depth understanding of the methodologies, technologies, and algorithms currently used in machine learning. Students will be introduced to the theory behind a range of machine learning tools and practice applying the tools to different applications. It explores topics such as classification, linear models, supervised and unsupervised learning in conjunction with applied and theoretical machine learning concepts. Students complete practical activities using machine learning algorithms and methods.

Pre-requisite: MFA501 Mathematical Foundations of AI

Assessment Tasks: Notebook with mark-up, presentation, model selection

Delivery Mode: On Campus, Online