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Return to Course Master of Information Technology IT4008.10 Internet of Things This subject introduces students tomodern concepts related to the Internet-of-Things (IoT) paradigms, applications, architecture, and implementation requirements. It begins with the recent history of IoT technologies and discusses the increasing demand for connected devices, sensors, and actuators to gather real-time data across various industrial verticals. This subject also covers IoT network-related concepts, including the four-layer IoT reference model, network protocol requirements, and IoT protocol stacks. At the service level, topics such as IoT service platform management, industry standards, open-source technologies, and security management in IoT infrastructures are discussed. Finally, students will work on a design project to develop or enhance an IoT-based innovation. Previous Next

Return to Course Bachelor of Information Technology IT3800.10 – Data Science Applications This subject explores the applied practice of data science in industry and organisational contexts, combining data manipulation, statistical analysis, machine learning foundations, and cloud-based data workflows. Students learn how data science is used to extract insights from structured and unstructured data, support evidence-based decision-making, and develop predictive models for real-world business and operational problems. The subject focuses on the full data science lifecycle, including problem definition, data collection, preparation, analysis, modelling, and communication, with an emphasis on translating technical results into actionable insights for stakeholders. Students gain hands-on experience using Python-based tools, cloud platforms, and data visualisation techniques in applied industry scenarios. Ethical, security, governance, and responsible AI considerations are integrated throughout, alongside the development of professional communication skills for both technical and non-technical audiences. Through applied learning activities, students build the capability to contribute to industry roles in data science, analytics, machine learning, and data-driven innovation. Previous Next

Return to Course Master Of Engineering Management ENG4014.10 Engineering Quality Management This subject introduces students to the key frameworks and approaches to quality management. By the end of the subject, students are able to identify and apply quality management frameworks and approaches to new contexts and propose appropriate measures to address quality management issues in various contexts. The impact of quality on the role of engineers, generating value through quality, and the philosophies and frameworks of quality management set the foundation for the subject. Key topics include customer, workforce, and process focus, quality management systems, statistical methods and designing for quality, measuring for quality control, and process improvement, including Six Sigma and the DMAIC process. Strategic planning, knowledge management, and criteria for performance excellence are also covered, with insight into ISO 9000, Six Sigma, or Baldrige, and how to lead, build, and sustain performance excellence. Students engage in weekly class discussions and apply their knowledge to worked examples and case studies from both national and international contexts. Assessment tasks also provide students with the opportunity to gain contextualised knowledge relevant to quality management and develop communication and teamwork skills. Individual students assess their own competence using their Portfolio and by setting personal learning goals. Individual students set up a program-based professional portfolio, which is to track and facilitate professional learning and development across all subjects of the MEM program. This is done by self-assessing their competencies at the start of each subject/semester, and setting personal learning goals to work on the development of their skills and competencies, and to be prepared for the real world of work after graduation. Previous Next

Return to Course Master Of Engineering Management ENG4004.10 - Project Management This subject provides students with an understanding of the key processes and competencies required to successfully manage projects. Students gain an understanding of project management processes, including initiation, planning, execution, monitoring and controlling, and closing, with relevance to engineering projects. With reference to the Project Management Institute’s Project Management Body of Knowledge (PMBOK® Guide), students are introduced to the knowledge areas of project management, including scope, time, cost, quality, resources, communication, risk, procurement, stakeholder, and integration. By completing the assessment tasks, students gain contextualised knowledge that is relevant to the engineering profession and are able to transfer their learning and skills to other contexts. Individual students set up a program-based professional portfolio, which is to track and facilitate professional learning and development across all subjects of the MEM program. This is done by self-assessing their competencies at the start of each subject/semester, and setting personal learning goals to work on the development of their skills and competencies, and to be prepared for the real world of work after graduation. Previous Next

Return to Course Bachelor of Information Technology IT3040.10 – Data Mining This subject prepares students for industry transition by applying the principles and techniques of data mining to extract meaningful knowledge from large-scale organisational datasets. Students explore data mining processes, association rule mining, classification, clustering, web data mining, and data warehousing concepts, including ETL, warehouse design, operational data stores, and metadata management, while addressing user, organisational, and stakeholder information needs through effective analytical and technical approaches. By the end of the subject, students are prepared for industry transition by applying analytical skills to transform data into actionable insights that support business intelligence, data science, decision support, and data-driven organisational decision-making. Previous Next

Return to Course Bachelor of Information Technology IT3100.10 – Data Analytics and Visualisation This subject prepares students for industry transition by applying contemporary data analytics and visualisation practices through a practical, hands-on approach. Students learn to acquire, clean, analyse, and interpret organisational data using Python-based tools, covering core techniques such as exploratory data analysis, classification, clustering, modelling, pattern mining, and introductory text and network analytics, while ensuring insights address both user interpretation needs and technical data requirements. The subject emphasises visual storytelling, stakeholder communication, and responsible use of data, including ethics, governance, privacy, and AI considerations. By the end of the subject, students are prepared for industry transition by applying a structured data analytics workflow to deliver meaningful, interpretable, and actionable insights in professional contexts. Previous Next

Return to Course Master of Information Technology IT5007.10 Emerging Trends in AI This subject covers emerging trends and the future of AI. Students will discuss and analyse case studies based on real-world AI applications and emerging technologies. The ethical issues and security issues surrounding the AI applications and emerging trends will be assessed and appraised. Students will be able to apply tools, technologies, and techniques to analyse case studies and solve research problems. Students will develop knowledge on various AI technologies for Amazon, Microsoft, and Google Cloud. The fusion of AI with IoT and cybersecurity will be covered, also in retail and finance automation. The techniques and mechanisms to detect cyber security threats with AI, the trends of AI in medical field, AI for smart cities and offices, AIinmanu factoring, logistics, and supply chain, AI in marketing and retail including finance and automation, and the application of AI in defence technologies for electronic warfare will be covered. Case studies will enable students to enhance their knowledge of the various emerging AI applications. Previous Next

Return to Course Bachelor of Information Technology IT1050.10 – Database Systems This subject introduces the principles and practices of modern database systems. It begins with the fundamentals of relational databases, including entity–relationship modelling, relational schema design, functional dependencies, and normalization. The techniques for accessing data using relational algebra and relational calculus and use SQL in detail for data manipulation and retrieval are explained. The exploration of advanced topics in industry such as indexing, query optimization, and transaction management are discussed. Professionalism and ethical considerations in database design are emphasized. The subject also explores emerging technologies such as NoSQL databases (e.g., MongoDB) and cloud-based services (e.g., Azure SQL Database, Amazon), with hands-on experience in designing, implementing, and deploying solutions using industry-standard tools. Previous Next

Return to Course Bachelor of Information Technology IT2000.10 – Software Development This subject builds on IT1060.10 Introduction to Computer Programming by deepening students’ knowledge of object-oriented programming (OOP) using Python. Core concepts including encapsulation, inheritance, polymorphism, class design, and graphical user interface (GUI) development are reinforced through practical implementation. Students explore object-oriented design principles, software development methodologies, and the use of professional development environments to design, implement, test, and document maintainable software solutions with a focus on real-world application and user-based requirements. The subject prepares students for roles such as software developer, application programmer, and junior systems engineer. In addition to technical skills, the subject develops communication, teamwork, and foundational leadership capabilities, reflecting professional practices in collaborative software development environments. Previous Next

Return to Course Bachelor of Information Technology IT1010.10 – Statistics in Information Technology This subject introduces core statistical and quantitative methods used in business and industry decision-making, equipping students with practical skills in collecting, analysing, and presenting business and economic data. Students explore key concepts including measures of central tendency and dispersion, probability principles and distributions, as well as sampling, estimation, and hypothesis testing. Through hands-on use of Microsoft Excel and introductory statistical tools, they learn to convert raw data into meaningful insights that support forecasting, risk assessment, and evidence-based reporting. The subject prepares students for roles such as business, data, operations, financial, and marketing analysts, as well as junior risk consultants, with a strong focus on applying statistical reasoning to real-world organisational contexts across finance, supply chain, marketing, human resources, and strategic planning. Previous Next

Return to Course Bachelor of Information Technology IT3300.10 – Artificial Intelligence for Entrepreneurship This subject prepares students for industry transition by applying Artificial Intelligence and emerging digital technologies to innovation and entrepreneurship in modern industries. Students explore AI, cloud services, mobile computing, blockchain, and data-driven platforms to develop digital products and services, while examining opportunity identification, business model development, funding readiness, and responsible AI use, balancing user needs, market value, and technical feasibility. Through real-world case studies, students analyse how technology-driven ventures create value propositions and support growth. By the end of the subject, students are prepared for industry transition by applying entrepreneurial, technological, and communication skills to design, pitch, and prototype AI-enabled solutions in professional innovation contexts. Previous Next

Return to Course Bachelor of Information Technology IT1030.10 – Computer Organisation and Architecture This subject introduces the fundamentals of computer organisation, including the roles of the processor, main memory, and input/output devices, and how these components work together to execute programs. It explains programs as sequences of machine instructions and explores the relationship between machine language, assembly language, and high-level compiled languages. Students learn number systems and data representation, including arithmetic and logical operations, as well as how data is stored and processed within a computer. Key concepts such as memory organisation, cache structures, virtual memory, instruction representation, addressing techniques, and instruction execution at the machine level are also covered. The subject provides an overview of operating systems, focusing on how hardware and software interact to manage resources and ensure efficient operation. In addition, it introduces basic digital logic, including logic gates and circuits, and concludes with an overview of how artificial intelligence is influencing modern computer organisation. Previous Next