In the information era, more companies and organisations rely on data-driven technologies to provide better service quality. However, with the broader collection and deeper digging of data, social participants raise more concerns about information privacy and ethics in data processing. This module targets on delivering the knowledge and skills revolving around this topic. The contents include but are not limited to database hardware and software structure, data security in storage, information transferring safety, ethics in processing sensitive data, safety in cloud service, security frameworks and privacy regulations. The module will provide both theoretical knowledge and practical exposure to the students. Assessment method: 100% coursework.
Explore the fundamentals of network engineering in this comprehensive module. Learn the principles of designing, implementing, and managing computer networks, including LANs, WANs, and wireless networks. Dive into topics such as network protocols, routing, switching, security, and troubleshooting. Gain hands-on experience with industry-standard tools and technologies used in modern networking environments. The emergency of cloud computing has challenged the way networking is viewed. We will look at how to plan and implement networks in the cloud. The module will provide both theoretical knowledge and practical exposure to the students and equip for the world of work. Assessment method: 100% coursework.
The module introduces neural networks and deep learning, one of the key topics in modern applied AI. The module will provide the student with an in depth understanding of all the components of neural networks, from the different computational building blocks to the functions to be optimized and finally to the different optimization strategies. The module will present how neural networks can be trained and validated to learn from data to solve specific tasks, and how they evolved into deep neural networks, convolutional neural networks and graph networks, presenting their major architecture concepts. The module will introduce some core concepts of the legal aspects of data protection and decision fairness in the application of deep learning technologies. Assessment method: 100% coursework.
Computer systems worldwide are systematically falling prey to rampant hacking. This hacking, characterized by its widespread nature and flawless execution, results in attackers infiltrating systems, plundering valuable assets, and leaving behind no traces of their intrusion. The objective of ethical hackers is to assist organizations in proactively defending against malicious attacks by simulating such attacks themselves, all while adhering to legal boundaries. This approach is founded on the principle of understanding and anticipating the tactics of potential adversaries, akin to catching a thief by thinking like one. This module will help students to develop the necessary skills Needed to succeed as a Penetration Tester and Ethical Hacker. Assessment method: 100% coursework.
To develop an in-depth, critically evaluative knowledge of concepts of security in networks and systems and the acquisition of knowledge about the processes, techniques, and security technologies to achieve an end-to-end security system. The course will analyse the security requirements and the vulnerabilities that threaten the smooth functioning of a computer system / network and will inform about ways of prevention, protection, recognition, and treatment of malicious attacks using appropriate technologies and security tools. Assessment method: 100% coursework.
Future Internet technologies comprise set of enablers to deal with the limitation of existing Internet. This includes but not limited All-IP Networking Architectures, evolution towards 4G+/5G networking architectures, open-based networking technologies, Cloud Computing challenges and IoT technologies and its interworking with 4G+/5G networks. The module will provide both theoretical knowledge and practical exposure to the students. Assessment method: 100% coursework.
The module will provide students with the critical skills, knowledge and analytical abilities needed to identify and address ethical challenges as they arise in practice from the application of AI. The module will engage with the ethical and societal challenges of AI and is thoroughly informed by the knowledge, theories and methods of established academic disciplines from philosophy to computer science. Industrial seminars on AI applications will complement the content of the module, exposing the students to the challenges of developing an AI application, considering the short- and long-ranging societal fallout. Assessment method: 100% coursework.
The module requires students to undertake an independent piece of research / development work, investigating in depth a subject, in which they have a particular interest and of their own selection. The dissertation assesses students’ ability to integrate information from various sources, to conduct an in-depth investigation, where necessary specify, appropriately develop bespoke software/technology-based solutions, to critically analyse results and information obtained and to propose improvements/further work. Each student will submit a dissertation of between 12,000-15,000 words. Assessment method: 100% coursework.
The placement gives you the opportunity to spend a year in the workplace, honing your transferable skills and proving your academic learning in the development of real-world systems. The assessment of the placement is designed to support and accredit the experience by formalising personal development outcomes, and by contextualising prior learning. Regular on-line contact with tutors, peer-contact and placement support will be maintained throughout the year. Assessment: 100% coursework.
