Advanced Computer Science (with optional Placement/Project year) MSc

1. Projects which will involve the application of methods and equipment introduced in taught modules, will be based on subjects agreed in principle with the Postgraduate Dissertation Coordinator and potential supervisors.
2. The research dissertation may be University-based or carried out in the employer’s workplace, or through a work placement where a local organisation has a direct role in facilitating the project.

To afford students the opportunity to experience the complete life-cycle of a successful and significant research-based project

To provide real-world experience of meeting the requirements of academic and professional standards, including high-level writing and referencing skills.

To demonstrate to peers and to current and potential employers the student’s ability to carry out good quality academic research, in a particular field, which is relevant to their programme of study. This may involve the application of existing research within a novel context.

To include:

• Time management, library skills and literature search
• Evaluation of information sources
• Critical analysis of information
• Ethical issues in science, technology and engineering research (including intellectual property and plagiarism)
• Writing for research: styles and rules for presentation (including referencing standards)
• Choosing a research area and evaluating source material
• Hypothesis formation
• Research approaches and methodologies
• Design and application of questionnaires & interviews
• Quantitative and statistical tools for researchers (e.g. R, Python, SPSS)

• To clarify the distinctions between undergraduate and postgraduate level work and expectations
• To increase students' experience in order to conduct a professional study and to use sampling procedures and analysing techniques.
• To improve students' appreciation of time management and how to conduct a literature search
• To reinforce students' research skills
• To consolidate students' appreciation of professional issues such as copyright and ethics

• Applying advanced knowledge of user-centred design principles
• Information architecture
• Progressive enhancement
• Applying user interface design patterns to professional standards
• Multidisciplinary design activities, problem-solving and design iteration
• Advanced usability testing and evaluation
• Issues in UX and emerging technologies

• To demonstrate effective use of advanced user-centred design methodologies
• To design standards-driven and scalable information architecture for interactive systems
• To apply progressive enhancement techniques
• To participate in professional team-based design sprints
• To undertake advanced usability testing and evaluation of interactive systems

Computability, Time and space complexity, asymptotic notation, polynomial and exponential time

Determinism, Nondeterminism, Complexity classes including P, NP, Co-NP, the polynomial time hierarchy and PSPACE

Reductions, proofs and practical case studies

Algorithmic approaches such as meta-heuristics, natural computation and mathematical programming

By the end of this module, students should be able to apply a range of problem solving techniques and to analyse the performance of such techniques with regard to resource consumption and accuracy. Students will gain a grasp of the limits of computation and of the complexity of both theoretical and real word problems as well as learning how to adjust problem solving processes to tackle highly complex scenarios.

The module draws on the research expertise in bio-inspired computing that exists within the Department of Computer Science to instruct students in an exciting area of computer science that is growing in research and commercial importance. The module content will include lecture material on:

-Evolutionary and genetic algorithms.

-Swarm behaviour

-Cellular automata 

-Chaos and fractals

-Neural computation

-Agent based models

-Complex adaptive systems

-Biologically inspired optimisation and behaviour search

To study elements of bio-inspired computing techniques which can be applied in simulation and modelling. To provide an overview of existing platforms and frameworks for bio-inspired computing. To gain experience and practical application of research and development techniques related to bio-inspired computing.

• Evolution of Robotics
• Microcontrollers: Arduino and Raspberry Pi
• Computer Vision
• Agents and Multi-Agent Systems
• Machine learning and robotics

• To introduce the concept of artificial intelligence (AI) and to evaluate its role in the development of robotics.
• To introduce theoretical approaches to the development of intelligent robots.
• To undertake practical tasks to demonstrate how AI techniques can be implemented for robotics.
• To analyse methods for designing and deploying robotic systems.
• To critically evaluate the ways in which intelligent robots can be used in real world situations

• Digital system forensics
  • Disk
  • Memory
  • Mobile
  • Cloud
• Live forensics
• Encryption and obfuscation
• Malware analysis and investigation
• Network forensics
• Anti-forensics
• Methodologies, approaches, and techniques
• Cyber Threat Intelligence and attribution
• Incident Response
• Ethical issues in digital forensics and incident response

This module aims to introduce the student to the need for and uses of digital forensics and incident response from an organisational security perspective.

The aim of this module is to introduce, study, understand and practice digital forensics techniques, and to understand the limitations of common techniques.  It aims to develop in the student an appreciation and understanding of anti- and counter-forensics, including falsification of data.  Finally, it aims to build the students' understanding of malware, how it operates, and practices to deal with it.

Students will gain an understanding of Incident Response and Cyber Threat Intelligence.

• Network security and attacks
• The current threat landscape
• Social engineering
• Penetration testing tools
• Active defence
• Threat hunting
• Defensive strategies and tools 
• Hack back and the legal implications
• Hacker tools
• Penetration testing; methodologies, approaches, and techniques
• Penetration test reporting
• Ethical issues in penetration testing and active defence

This module aims to:

• introduce the student to the need for and uses of penetration testing and active defence from an organizational security perspective;
• introduce, study, understand and practice active defence and the limitations of common techniques. This will also look at relevant tools and the legal aspect of 'hack back';
• help the student study, understand, and practice penetration testing techniques, developing skills in 'access' over networks, and how attackers look at a target; 
• the relevant skills, knowledge and usage of hacker tools and how to stop/deter attackers

These will be built upon to allow the student to better understand network and holistic defenses and to be able to design secure interconnected systems.

Embedded Systems and Field Programmable Gate Array (FPGA) Technology

• Concurrent assignment statements and unintended memory
• Adopting proper hardware description language (HDL) coding style and taking a divide and conquer approach for code development
• The need for design simplification.
• Regular sequential circuit block system and registers 
• Building test-benches for sequential circuits
• Timing, clocking, operating frequency and clock tree considerations
• The Finite-state machine (FSM), its representation and FSM HDL code development
• The Finite-state machine with data path (FSMD), its representation and FSM HDL code development

Internet of Things (IoT)

• Automatic Identification Technology and Radio-frequency identification (RFID)
• Wireless Sensor Network
• Location System
• Internet and Mobile Internet
• Wireless Access Technology
• Big Data, IoT & Cloud Computing
• Information Security for IoT
• IoT Application Case Studies
• Arduino Opla, Espressif System on Chip (SoC) & Raspberry Pi IoT technologies

The Embedded Systems part of this module aims to develop the skill in students of digital systems design with the VHDL hardware description language (HDL) and Field Programmable Gate Array (FPGA) reprogrammable and fast prototyping technologies. Students will be able to produce design, synthesis of circuits and implement system on chip (SoC) using modern electronic design automation (EDA) tools.

The Internet of Things (IoT) contents aim to develop the advanced practical skills in building and designing IoT related components and network systems, going from the sensors layer to the cloud processing. This part also develops expertise in the use of a hardware/software tools to create and simulate practical systems, considering big data, energy consumption control and network security aspects.