MSc Computer Science

COMM107: Algorithms and Architectures

This module will introduce you to algorithms, the fundamentals of their design, and their importance within computer science. You will learn how to design and implement efficient algorithms, as well as evaluating algorithm complexity. You will also learn about key concepts concerning computer architectures, operating systems and networks – including memory management, storage concepts, process control and software execution.

The aims of this module are to introduce you to the skills needed to design, construct and manage the operation of software running on modern computing systems. You will understand the importance of designing efficient algorithms and will be able to analyse their runtime complexity.

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COMM108: Data Systems

This module will introduce you to the ways in which data is stored within a computer system. You will learn about a variety of types of database, including those based on the structured query language (SQL) and those designed to structure data differently (so-called NoSQL databases). You will develop a theoretical understanding about how data should be organised, and will learn how to access and modify the data in a database from an application.

The aim of this module is to instil students with an appreciation of the different ways that data can be stored. By introducing multiple approaches (e.g. SQL-based and NoSQL) students will learn how to select the most appropriate storage for a given application, taking into account the complexities around accessing and writing data. Students will also learn how to construct software to connect an application to a database securely.

The module will also cover concurrency control, backup and recovery, user management, and web development with databases, The module will also introduce modern concepts concerning data systems, which might include big data, the cloud, data warehousing, blockchain, decentralised systems, and governance.

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COMM109: Programming with Python

This module will introduce students to the fundamentals of constructing software using the Python programming language. You will learn how to decompose problems into components that can be implemented to provide a software solution, as well as how to control program flow and represent data within software. Having learned the fundamentals of Python coding you will be introduced to exception handling, Python classes, and be introduced to principles of software development and testing.

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COMM110: Software Development

This module builds on the programming experience you have already obtained and provides you with experience of the cutting-edge software development skills you will need to take your abilities to the next level. You will explore topics such as product requirements and software design, software verification and validation, effective teamwork in software engineering, and software engineering tools. As part of the assessment for this module you will undertake a team project in which you will put your learning into practice to deliver a substantial software project.

The aims of this module are to move you from being able to code to being capable software developers who can function usefully in a software development team. You will learn how to work together to design robust and verified software that meets user requirements.

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COMM514: Research Project

In this module, you will work on a research problem in an area relating to your programme of study, applying the tools and techniques that you have learned throughout the modules of the programme. This is an independent project, supervised by an expert from the relevant area, and culminates in writing a dissertation in the form of a research paper, describing your research and its results.

Research topics can be selected from across the breadth of computer science, data science and related topics. The project may include theoretical analysis, as well as practical software implementation.

This module aims to give you in-depth experience of research in an area relating to your programme of study. It will help you prepare for projects both in an industry or commercial setting, as well as in further postgraduate research work, such as a PhD. The module builds on the knowledge and skills you have acquired in the taught modules of the programme to allow you to investigate an area of particular interest to you. It aims to give you experience of many aspects of research work, including problem formulation, literature review, planning, tool development, experimentation, analysis and presentation of results.

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ECMM462: Fundamentals of Security

Our modern life depends on the security of computerised systems ranging from social aspects (e.g. phishing) to technical and mathematical aspects (e.g. access control, encryption). In this module, you will learn the fundamental concepts required for starting a career in various areas related to security (e.g. cyber security, data security, information security, computer security). You will learn core security concepts (e.g. authenticity, confidentiality, anonymity, privacy) and core technologies (e.g. encryption, authentication, authorisation). Moreover, you will learn the basic attacks on security systems and approaches for reasoning about the correctness of security techniques.

The aim of this module to create awareness of the need for security and privacy in modern life, and to introduce the fundamental security and privacy mechanism used in modern computer systems. We will explore topics such as fundamentals of computer security, technology and principles of network security, cryptography, authentication and digital signatures, access control mechanisms, privacy, and anonymisation.

In more detail, the aims of the module are to give you an understanding of:

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SOCM033: Data Governance and Ethics

Data science, machine learning, artificial intelligence and 'big data' have become central to every aspect of social life. How can these complex and powerful technologies best be managed and governed for the benefit of society now and in the future? In this module you will: (1) identify some of the main risks and ethical/legal challenges involved in the widespread automation and digitalisation of services characterising 21st century life (for example, the clash between individual desire for privacy, frameworks for data ownership and the institutional commodification of personal data); (2) examine whether and how such concerns can be handled; and (3) discuss the responsibilities of data scientists and other producers of technologies for data analysis towards their proper use.

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BEMM190: Digital Transformation

This module will introduce you to the fundamentals of digital transformation through study of a range of practical examples. Organisations must position themselves for success in the digital era to be sustainable. For new ventures, it means creating structures and working practices appropriate to the dynamic environment. For established organisations, it means transforming existing structures and ways of working to meet current and future needs while continuing to meet the expectations of existing clients, employees and other stakeholders. Consequently, digital transformation activities are becoming increasingly strategic across public, private and third sectors.

You will also assess the implications for career development within these disruptive environments. This means building the digital skills required for success such as effective workplace communications across hybrid locations, the use of collaborative online tools, and the importance of ethical behaviour and wellbeing.

This module will help you to:

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COMM042: Introduction to Computer Vision

How do we recognise objects and people? How can we catch a ball? How do we navigate our way from our desk to the coffee machine, without bumping into each other? These seemingly simple tasks have represented a challenge for AI scientists for decades. Recent developments in computer vision have seen significant improvement in important applications (face detection in cameras, body tracking, and autonomous cars).

This module will provide you with the fundamentals of computer vision, covering the essential challenges and key algorithms for solving a variety of vision problems. The course will provide both theoretical grounding in the relevant theories and a blend of classical and state-of-the-art approaches to computer vision problems. The course will focus on practical applications of computer vision and cover a broad range of problems, from low-level image processing to object recognition, tracking and 3D vision.

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COMM111: Foundations of Human-Centred AI

You will study foundational concepts in how to design Artificial Intelligence (AI) systems that interact with humans. This will involve learning about human psychology including computational theories of how people represent and process knowledge, learn and work together. You will learn about topics including, how people make decisions, how they perform perceptual/manual tasks, how human vision works. You will use these theories to build and critically evaluate Artificial Intelligence systems that work with people.

You should take this module if you are interested in going on to a masters/research degree and/or in the rapidly expanding number of career pathways that involve designing AI to work with people. For these careers learning about human psychology is vital to designing systems that, for example, people find useful but not controlling and people find engaging but not addictive. For example, answers to the following questions require an understanding of the psychology of the user. How can AI be fine-tuned to human preferences and emotions? How can an AI system learn about an individual person’s goals and preferences? How can it learn about their emotions and feelings about others? Answers to these questions can help improve AI systems that work with people in the workplace and the home.

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COMM112: Design Methods for Human-Centred AI

Learn the skills needed to practice Human-centred design of Artificially Intelligent systems. You will learn how to use computational design thinking to empathise with people, ideate, prototype and evaluate AI systems. You will learn how to abstract AI problems by engaging with people, communities and contexts.  You will apply methods from Human-Computer Interaction to engage with users through participatory design practices.

Having used these methods to abstract Human Centred AI problems, you will learn how to investigate prototype solutions and critically analyse their strengths and weaknesses, both from a computational perspective and a human perspective.

You will attend a weekly class in which an expert in Human-centred AI will lead discussion of an aspect of Human Centred AI design and its implications for how relevant Artificial Intelligence technologies are likely to impact people.

This course is a hands-on, practice-oriented approach to learning Human-centred AI (HCAI) design, with a strong emphasis on the evaluation of AI systems from both technical and human perspectives. Methods covered will include design thinking, participatory design, A/B testing, think-aloud protocols, diary studies, eye tracking studies etc. These tools provide students with the skills required to work with people to understand their needs and desires, understand how and why they perform tasks as they do and design AI systems that work with and for them.

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ECM3408: Enterprise Computing

The vast majority of businesses now rely upon well-designed, functional, efficient and secure IT systems to carry out their day-to-day operations and to guide their business strategy.  This module introduces you to the techniques required to enable the development of systems that can operate across multiple sites, perhaps even multiple countries, in a secure and efficient manner.   In addition, the module highlights the issues and opportunities that can arise from the creation and storage of large-scale datasets.  This module will be appropriate for any student interested in the development of enterprise-level software who is studying a programme with significant programming content.

The aim of this module is to introduce you to the enterprise-level techniques used to implement large-scale distributed systems in heterogeneous environments and to consider issues such as interoperability, performance, security and persistence of information within those systems. The module also aims to provide you with an understanding of the latest internet technologies used to assist enterprises in their operation, such as service-oriented architectures, web services and cloud computing.

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ECMM447: Social Networks and Text Analysis

The rise of the Web has created huge datasets relating to the interaction of users and online content. Much of this content is relational and is best understood using a network perspective (for example, hyperlinked web pages; users linking to content; users linking to users on social platforms). Much of this content consists of unstructured text (for example, webpages, blogs, social media posts) that requires computational methods for analysis at scale. In this module you will learn the core principles of social network analysis and computational text analysis, enabling you to gain insight from the rich data available on the Web.

The aim of this module is to equip you with a range of knowledge and skills needed to make effective use of data from the Web. This module will cover various topics in social network analysis and text analysis, which together allow relational and unstructured text data to be analysed at scale. The module will be taught using the Python language and various open-source packages.

The module will be taught in weekly lectures and associated practical work, together with individual self-study and labs. Lectures will introduce the topics of social network analysis and text analysis, accompanied by practical exercises based on lecture material.

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ECMM461: High-Performance Computing

The demand for ever-increasing computational power drives the development and exploitation of high-performance computing that underpins leading edge research in computationally intensive engineering technologies fields. This module is designed to equip you with a solid foundation and useful skills in high-performance and distributed computing. In this module, you will learn about current high-performance computer architectures and how the computer architecture influences the performance of algorithms and programs. You will also develop skills in parallel algorithm design and parallel programming, and will gain experience of using a high-performance computing system.

This module aims to provide you with a thorough grounding in parallel programming and the architectures used in high-performance computing. After presenting the fundamental ideas and basic concepts of high-performance computing, the module outlines the architectures, components and parallel programming of high-performance computers. The module will introduce you to recent developments and future trends in architecture and algorithms in high-performance computing.

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ECMM463: Building Secure and Trustworthy Systems

Building secure and trustworthy systems, i.e. systems that are hard to attack and protect the privacy of their users, are extremely hard to build. In this module, you will learn the foundations of building secure (software) systems ‘right from the beginning’. You will learn how to assess the threats of a system that need to be mitigated while building it, the risk assessment of vulnerabilities, as well as various approaches (e.g., defensive programming) and techniques for building secure systems. The module focuses on defensive security techniques that might be used by “blue teams.”

This module aims to give you a broad understanding of techniques for assessing the risks a modern IT system is exposed to. Driven by these risks, we will discuss several defensive security techniques for building security and trustworthy (software) systems. In more detail, the aims of the module are to enable you to assess the security of software architectures understand the principles of secure software architectures understand software vulnerabilities, their causes, and impact to develop secure software using defensive programming techniques to understand the principles of security testing and verification techniques.

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ECMM464: Security Assessment and Validation

Even if systems have been developed with security in mind, their security needs to be assessed regularly, as, e.g., new attacks might be developed. Thus, assessing and validating the security of systems, e.g., penetration testing is an important part of cyber security. In this module you will learn the theory and practice of assessing the security of systems and applications both using manual techniques as well as automated approaches. The module focuses on offensive security that might be used by “red teams.”

This module aims to give you a broad understanding in analysing the weaknesses of a system, i.e., the areas an attacker would most likely attack a system. Driven by the discovered weaknesses, we will discuss several offensive security techniques, I.e., simulate how a threat actor (attacker) might gain access to a system or the data processed by a system. In more detail, the aims of the module are to enable you to assess the security weaknesses of a system develop a strategy how to attack a system understand the both the social and technical foundations for attacking systems or organisations understand the ethical responsibilities of an offensive security researcher.

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ECMM422: Machine Learning

Machine learning has emerged mainly from computer science and artificial intelligence, and draws on methods from a variety of related subjects including statistics, applied mathematics and more specialized fields, such as pattern recognition and neural computation. Applications are, for example, image and speech analysis, medical imaging, bioinformatics and exploratory data analysis in natural science and engineering. This module will provide you with a thorough grounding in the theory and application of machine learning, pattern recognition, classification, categorisation, and concept acquisition. Hence, it is particularly suitable for Computer Science, Mathematics and Engineering students and any students with some experience in probability and programming.

In this data-driven era, modern technologies are generating massive and high-dimensional datasets. This module aims to give you an understanding of computational methods used in modern data analysis.

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