Master of Information Technology

This subject explores the intersection of advanced Information Technology (IT) and Artificial Intelligence (AI). It focuses on developing essential problem-solving skills and ethical practices for IT professionals. Students will delve into IT research analysis, AI techniques, and logical reasoning. They will also practice programming skills and learn how to analyse, implement and apply AI techniques and algorithms.

Mathematical statistics, a branch of mathematics deals with models that establish relationships between data and theory. The models involve a random, unpredictable component, transforming numerical data into valuable information for making evidence-based judgments. This subject comprises of mathematical concepts including estimation and hypothesis testing, as well as their practical applications in areas such as sports, market research, finance, forensics, and medical studies. Students delve into fundamental topics such as probability, distribution, and random variables, along with statistical inferencing, data analysis, and their application in AI and data science using relevant software.

This subject equips students to develop the knowledge and skills in the conceptual, technical, and managerial foundations of system requirements and modelling. Students will learn how to design a set of system requirement specifications using use cases and user stories. Students will apply contemporary analysis and modelling techniques with a user centred approach to design intelligent systems that address complex business problems. By the end of the subject, students will gain skills in system requirements gathering and modelling techniques. Students will develop system design, user interactions and a system prototype guided by industry standard, quality assurance and professional practice frameworks.

(Cyber Security Major) This subject provides an in-depth study of Network Communications and Architectures, with an emphasis on the Concepts, Topology and Architectures for the organisation networks. Students will learn about the fundamentals, analysis, and troubleshooting of network and communication Issues, as well as the network Security and Privacy Issues. The subject will cover the Network Services, Corporate and Datacentre Architectures, Network Devices, Routing Technologies, and Bandwidth Management, SDN Controllers and Data Centre Concepts, Network Function Virtualization (NFV), Network Hardening Techniques, Network Troubleshooting Methodology, and Troubleshoot General Network Issues.

(Data Analytics Major) This subject provides the basics of data mining and its applications in different business scenarios. It introduces students to different data mining techniques to analyse complex datasets, discover trends and patterns and forecast scenarios that evolve over time. Students will be proficient to develop data mining models using industry standard tools and provide intelligent solutions for real-world problems. Students will research, evaluate, and validate the data mining models and techniques employed and reflect on the ethical, legal and security impacts of data mining.

The aim of this subject is to provide students with a comprehensive understanding of advanced database technologies and their roles in IT specialist areas such as cyber security and data analytics applied to real-life scenarios. Students will research and explore the relational and non-relational database fundamental theories and applications. This subject equips students with the knowledge to leverage structured query language (SQL) and NoSQL databases for diverse data storage and retrieval needs. Furthermore, the subject includes advanced topics such as data warehousing, database security, machine learning integration, big data technologies, and ethical considerations in data management to prepare the students for the complexities and challenges of modern data-driven environments.

This subject focuses on advanced project management theories, principles, and practices with an emphasis on industry standard methodologies and frameworks, Students will learn to apply PMBOK framework, Agile project management methodologies, project integration management and governance in professional scenarios. In the context of project management practice, students are required to adopt the mindset of a project manager, developing advanced skillsets in business agility, stakeholder management, communications and change management. With the considerations of ethical, social and security issues in project management, students will be able to learn how to manage risks in the lifecycle of complex IT projects.

This subject provides students with the knowledge of how research is conducted in Information Technology (IT) and the commonly used research methods in the field, particularly in Cyber Security and Data Analytics. Students will acquire the necessary skills to critically evaluate published research, identify and formulate research questions, plan and implement a complex research project design and acquire an understanding of and appreciation for research and scholarship ethics. They will be introduced to data collection and data analysis techniques that are appropriate to their specific subdisciplines.

(Cyber Security Major) This subject provides an in-depth study of the principles underpinning the Cloud and IoT Security architectures, with an emphasis on the attack types, privacy, and mitigation techniques for both Cloud and IoT systems. Students will learn about the design, analysis, and implementation of security in the Cloud and IoT environments, as well as their social, ethical and privacy implications.

(Data Analytics Major) This subject specialises in the intersection of business process management (BPM) and advanced process analytics. This subject is designed to equip students with the skills to harness the power of process analytics and artificial intelligence (AI) in the realm of BPM. Students will research on practical environments and industry environments and explore how to collect, analyse, and interpret data to make strategic decisions in business process optimisation. The curriculum includes hands-on experience with industry tools for Data Modelling, process analytics, and project management emphasising their use in real-world business scenarios. Ethical, legal, and societal considerations in process analytics will be a cornerstone of the subject, guided by the professional practices and ethical standards. On completing this subject, students will be adept at leveraging data insights for enhancing business efficiency and innovation in a rapidly evolving digital landscape.

Applied Research Project 1 is a crucial component of the student’s academic journey, marking the transition from theoretical learning to professional practice in IT. This subject allows students to synthesize and apply the knowledge and skills acquired throughout their program. Central to this subject is a substantial, discipline-specific applied research project designed to develop a research proposal for solving a complex IT problem using strategic planning and Agile project management skills crucial for professional success. Students are responsible for the initial design, planning, and organization of the project, with a focus on research, teamwork and collaboration with industry to provide real-world relevance and practical experience. The project culminates with the presentation of a detailed research proposal and project plan for an intelligent IT solution, including both written reports and oral presentations. This not only enhances students' communication skills but also prepares them for the complexities of professional project execution. Upon successful completion, students will progress to Applied Research Project 2, where they will critically evaluate and implement their IT solution and deliver their project as they transition to the professional world.

(Cyber Security Major) This subject provides an in-depth study of modern cryptography and data security, with an emphasis on the role of AI in these fields. Students will learn about the design, analysis, and implementation of cryptographic protocols and systems, as well as the use of AI techniques for data security and privacy. The course will cover both traditional cryptographic techniques as well as advanced topics such as secure multi-party computation, differential privacy, and federated learning.

(Cyber Security Major) This subject provides an in-depth study of Digital and Cyber Risk Management, with an emphasis on Enterprise Risk Management (ERM) standards and regulations. Students will learn about cyber threats and enterprise risks, as well as the contemporary environment issues and governance. They will develop strategies to monitor, detect and report cyber-attacks and risks as well as to apply response, recovery and hardening techniques in real world scenarios.

(Data Analytics Major) This subject provides an in-depth exploration of fundamental concepts and technologies underpinning intelligent systems in web and mobile data mining. Students will gain a comprehensive understanding of the seamless integration of artificial intelligence (AI) techniques, machine learning, and data analytics into the landscape of web and mobile platforms. It focuses on understanding how to extract meaningful information from datasets, analyse user behaviour, and apply AI methodologies to derive insights for strategic decisions. The curriculum covers a diverse range of topics, including the examination of tools and methodologies for collecting, processing, and analysing data within the context of intelligent web and mobile data.

(Data Analytics Major) Building upon previous analytics topics such as Data Mining, this subject explores Artificial Intelligence techniques such as Machine Learning and introduces contemporary methods in AI computing such as Chatbots, NLP and Deep Learning. Students will learn the theory and applications of Machine Learning, how to design, create, and evaluate commonly adopted Machine Learning algorithms in based on supervised and unsupervised techniques. This subject will also provide students with practical experience using standard tools in interpreting, designing, and constructing effective and business relevant visualisations considering Storytelling, Cognitive Load and Pre-attentive Attributes in the context of Machine Learning.

Applied Research Project 2 marks the culmination of the student's academic journey, providing a crucial opportunity to apply and integrate the knowledge and skills developed over the course of their studies in IT. Building on the foundation established in Applied Research Project 1, this subject focuses on the practical execution of their research proposal and project plan. It challenges students to implement their project effectively, adjust to real-world variables, and solve complex problems in IT dynamically with relevant AI techniques for delivering intelligent solutions. This phase is pivotal in demonstrating how theoretical concepts are applied in practical industry scenarios, emphasizing adaptability, intelligence and innovation.

As a concluding academic exercise, Applied Research Project 2 enables students to demonstrate their comprehensive understanding and application of their discipline-specific knowledge through the successful completion of a significant applied research project for the chosen industry with a tangible development of their skills and readiness for professional practice. The completion of this project signifies their transition from academic learning to professional development, preparing them for their future careers with a robust and real-world project experience.

(Cyber Security Major) In an era of rapid technological advancements, this unit provides a comprehensive understanding of two essential technology facets: smart systems and blockchain. Smart systems, comprising of the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML) and smart contracts, are revolutionising industries globally with their ability to enhance efficiency, productivity, and user experience. At the same time, blockchain technology, known for its decentralised and secure nature, is increasingly shaping business and societal operations. This unit will explore the intersection of these technologies, highlighting the ways in which they can work in unison to build innovative, robust and secure solutions.

(Cyber Security Major) In this age of swift technological progress, this subject focusses on the discovery and mitigation of vulnerabilities on systems and offers a thorough insight into two critical aspects of technology: Penetration Testing and Digital Forensics, Penetration Testing delves into the realm of cybersecurity, exploring tactics and countermeasures in digital environments while studying the potential threats, vulnerabilities, and the evolving landscape of cyber-attacks. Digital Forensics, on the other hand, focuses on the investigation and analysis of digital crimes, employing intelligent techniques to recover, analyse and preserve evidence from electronic devices. This subject will explore the synergy between these fields, emphasising how they collectively contribute to creating more secure and resilient digital systems. It will underscore the importance of rising cyber threats and the application of forensic methodologies to develop comprehensive and adaptive solutions for safeguarding digital infrastructure.

(Data Analytics Major) This subject explores the theory, concepts and architectures of Big Data and Cloud Computing. Students will learn about the underlying technologies and tools, and apply them along with AI techniques to analyse large datasets in cloud environments. Students will be able to create data pipelines that require distributed processing capabilities on a large volume of data in the Cloud for providing analytics solutions for real-life situations. In addition, students will understand the fundamental knowledge of ethical and privacy considerations of data capture, storage and their use in different business contexts.

(Data Analytics Major) IoT and Blockchain Intelligence is a unit designed to explore the integration of Internet of Things (IoT) and blockchain technologies with an emphasis on distributed machine learning. This course delves into how distributed machine learning complements the decentralized nature of both IoT and blockchain, enhancing the intelligence of these systems. Students will learn about the fundamentals of IoT and blockchain, understanding how interconnected devices in IoT networks can securely transmit data using blockchain's immutable ledger system. The unit emphasizes the application of distributed machine learning algorithms to analyse and derive insights from vast amounts of data generated by IoT devices. This approach not only ensures enhanced security and data integrity but also fosters efficient real-time decision-making. The course also covers the challenges and potential solutions in implementing these technologies, preparing students for the evolving landscape of digital interconnectivity and smart technology. This comprehensive unit aims to equip learners with the skills to innovate in the field of IoT and blockchain intelligence.