Cybersecurity and Machine Learning, _MSc

Programme Fees

Fee information

Fee category	Cost
EU / International students	£27,000
Tuition Fees for 2024/25 Academic Year
UK	£12,200
Tuition Fees for 2024/25 Academic Year

Semester 1

Compulsory Courses

Machine Learning (CS5062)

15 Credit Points

This course will deliver the most sophisticated Machine Learning methodologies and algorithms which would be illustrated across a wide range of applications including but not limited to images, videos, health, time series data, language processing, etc. This course provides students with the Machine Learning principles for continuing learning and working in the area of Data Science and Artificial Intelligence.

Detailed course information

Optional Courses

• Students must select ONE of CS502L Cybersecurity Fundamentals OR CS502B Security in Emerging Networks
• Students must select ONE of CS502M Security Analytics with Artificial Intelligence OR CS502C Enterprise Security Architecture
• Students must select ONE of CS5063 Evaluation of AI Systems OR CS5079 Applied Artificial Intelligence

Cybersecurity Fundamentals (CS502L)

15 Credit Points

This course presents the fundamental concepts of Cyber Security, including but not limited to cryptography, network protocols, access control, authentication, security management and web security. This course provides students with the Cyber Security principles for continuing learning and working in the area of Cyber Security.

Detailed course information

Security in Emerging Networks (CS502B)

15 Credit Points

This course will cover emerging technologies in cybersecurity such as Software-defined Networking (SDN), Internet of Things (IoT), and Blockchain. It will deliver the role of emerging technologies in cyberspace, what impact we will have on our legacy system and how we can remain agile and efficient. The course will provide a foundation for identifying the significance of technological advancements and cybersecurity issues, and challenges raised in adapting the 5G & beyond network.

Detailed course information

Security Analytics with Artificial Intelligence (CS502M)

15 Credit Points

This course provides an introduction to the analysis of cybersecurity data. It will show how to use tools and methods from data science and machine learning to perform such analysis. Broader issues at the interface of security and privacy with AI will be discussed.

Detailed course information

Enterprise Security Architecture (CS502C)

15 Credit Points

A major contributing factor to cyber risk is the lack of well-designed cybersecurity architecture that protects against ever-evolving cyber-attacks. A well-designed architecture provides a streamlined workflow for security and non-security practitioners, along with increasing the robustness of an organisation’s cybersecurity. In this course you will gain the advance knowledge to develop, design and analyse security solution architectures to meet your organisation's cybersecurity objectives.

Detailed course information

Evaluation of AI Systems (CS5063)

15 Credit Points

One of the biggest challenges in Artificial Intelligence is evaluating how well AI systems work. This course will provide students of our MSc in AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies; we will also look at software testing of AI systems.

Detailed course information

Applied Artificial Intelligence (CS5079)

15 Credit Points

This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments.

Detailed course information

Semester 2

Optional Courses

• Students must select ONE of CS552E Digital Forensics and Incident Management OR Blockchain and Smart Contracts
• Students must select ONE of CS551J Knowledge Representation and Reasoning OR CS551K Software Agents and Multi-Agent Systems
• Students must select ONE of CS552G Ethical hacking and web security OR CS552H Secure Software Development
• Students must select ONE of CS552J Data Mining with Deep Learning OR CS551H Natural Language Generation

Digital Forensics and Incident Management (CS552E)

15 Credit Points

Data breaches are everywhere, and cyber incidents can be extremely costly for an organization. Therefore, the speed at which you identify a violation and respond to the incident is critical to your data and systems' security. This course will provide technical and legal discussions on incident detection, investigation, response, and digital forensic techniques. It will walk you through best practices for everything from incident response to in-depth digital forensics. This will help the student identify vulnerabilities and better communicate breaches to those impacted.

Detailed course information

Knowledge Representation and Reasoning (CS551J)

15 Credit Points

Recent advances in AI have changed the perception of what machines can do, from on-line search to answering questions. An underlying feature of many AI systems concern how knowledge is acquired, represented, and reasoned with. Companies such as Google, IBM, and Facebook have been developing sophisticated tools for knowledge representation and reasoning. This module provides the theory and practice of knowledge representation and reasoning, also presenting cutting-edge technologies, libraries and tools. At the end of the course students will be able to design, implement and evaluate knowledge-intensive AI systems.

Detailed course information

Software Agents and Multi - Agent Systems (CS551K)

15 Credit Points

The global autonomous systems market is expected to be valued at over £13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in Tesla's self-driving cars, NASA space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product.

Detailed course information

Ethical Hacking and Web Security (CS552G)

15 Credit Points

This course will deliver approaches and methodologies used for carrying out and managing security and penetration testing, including but not limited to web applications, network protocols, common attacks and security countermeasures. The course will help the student build the ability to design secure systems and defend against intrusion.

Detailed course information

Secure Software Design and Development (CS552H)

15 Credit Points

Software bugs and vulnerabilities are the main source of threats to security. This course introduces students to design, development, testing and evaluating secure and dependable software. This course develops students both theoretical and practical skills to define, implement, examine, and manage secure software lifecycle. The course provides necessary skills needed for security professionals ranging from software architects, developers to penetration testers and IT Managers.

Detailed course information

Data Mining with Deep Learning (CS552J)

15 Credit Points

This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.

Detailed course information

Natural Language Generation (CS551H)

15 Credit Points

The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected.

Detailed course information

Semester 3

Compulsory Courses

Project in Cybersecurity (CS592A)

60 Credit Points

This course will provide students the opportunity to focus on a practical or theoretical problem and investigate the solutions. The research will be carried out under the supervision of a member of staff. Typical projects include improving, or adapting existing cybersecurity practices, theories, and techniques to solve different problems. Students will improve their problem-solving and communication skills, as well as broaden and consolidate knowledge obtained in other components of the degree.

Detailed course information

Programme Fees

Fee information

Fee category	Cost
EU / International students	£27,000
Tuition Fees for 2024/25 Academic Year
UK	£12,200
Tuition Fees for 2024/25 Academic Year

Semester 1

Optional Courses

• Students must select ONE of CS552E Digital Forensics and Incident Management OR Blockchain and Smart Contracts
• Students must select ONE of CS551J Knowledge Representation and Reasoning OR CS551K Software Agents and Multi-Agent Systems
• Students must select ONE of CS552G Ethical hacking and web security OR CS552H Secure Software Development
• Students must select ONE of CS552J Data Mining with Deep Learning OR CS551H Natural Language Generation

Digital Forensics and Incident Management (CS552E)

15 Credit Points

Data breaches are everywhere, and cyber incidents can be extremely costly for an organization. Therefore, the speed at which you identify a violation and respond to the incident is critical to your data and systems' security. This course will provide technical and legal discussions on incident detection, investigation, response, and digital forensic techniques. It will walk you through best practices for everything from incident response to in-depth digital forensics. This will help the student identify vulnerabilities and better communicate breaches to those impacted.

Detailed course information

Knowledge Representation and Reasoning (CS551J)

15 Credit Points

Recent advances in AI have changed the perception of what machines can do, from on-line search to answering questions. An underlying feature of many AI systems concern how knowledge is acquired, represented, and reasoned with. Companies such as Google, IBM, and Facebook have been developing sophisticated tools for knowledge representation and reasoning. This module provides the theory and practice of knowledge representation and reasoning, also presenting cutting-edge technologies, libraries and tools. At the end of the course students will be able to design, implement and evaluate knowledge-intensive AI systems.

Detailed course information

Software Agents and Multi - Agent Systems (CS551K)

15 Credit Points

The global autonomous systems market is expected to be valued at over £13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in Tesla's self-driving cars, NASA space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product.

Detailed course information

Ethical Hacking and Web Security (CS552G)

15 Credit Points

This course will deliver approaches and methodologies used for carrying out and managing security and penetration testing, including but not limited to web applications, network protocols, common attacks and security countermeasures. The course will help the student build the ability to design secure systems and defend against intrusion.

Detailed course information

Secure Software Design and Development (CS552H)

15 Credit Points

Software bugs and vulnerabilities are the main source of threats to security. This course introduces students to design, development, testing and evaluating secure and dependable software. This course develops students both theoretical and practical skills to define, implement, examine, and manage secure software lifecycle. The course provides necessary skills needed for security professionals ranging from software architects, developers to penetration testers and IT Managers.

Detailed course information

Data Mining with Deep Learning (CS552J)

15 Credit Points

This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.

Detailed course information

Natural Language Generation (CS551H)

15 Credit Points

The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected.

Detailed course information

Semester 2

Compulsory Courses

Machine Learning (CS5062)

15 Credit Points

This course will deliver the most sophisticated Machine Learning methodologies and algorithms which would be illustrated across a wide range of applications including but not limited to images, videos, health, time series data, language processing, etc. This course provides students with the Machine Learning principles for continuing learning and working in the area of Data Science and Artificial Intelligence.

Detailed course information

Optional Courses

• Students must select ONE of CS502L Cybersecurity Fundamentals OR CS502B Security in Emerging Networks
• Students must select ONE of CS502M Security Analytics with Artificial Intelligence OR CS502C Enterprise Security Architecture
• Students must select ONE of CS5063 Evaluation of AI Systems OR CS5079 Applied Artificial Intelligence

Cybersecurity Fundamentals (CS502L)

15 Credit Points

This course presents the fundamental concepts of Cyber Security, including but not limited to cryptography, network protocols, access control, authentication, security management and web security. This course provides students with the Cyber Security principles for continuing learning and working in the area of Cyber Security.

Detailed course information

Security in Emerging Networks (CS502B)

15 Credit Points

This course will cover emerging technologies in cybersecurity such as Software-defined Networking (SDN), Internet of Things (IoT), and Blockchain. It will deliver the role of emerging technologies in cyberspace, what impact we will have on our legacy system and how we can remain agile and efficient. The course will provide a foundation for identifying the significance of technological advancements and cybersecurity issues, and challenges raised in adapting the 5G & beyond network.

Detailed course information

Security Analytics with Artificial Intelligence (CS502M)

15 Credit Points

This course provides an introduction to the analysis of cybersecurity data. It will show how to use tools and methods from data science and machine learning to perform such analysis. Broader issues at the interface of security and privacy with AI will be discussed.

Detailed course information

Enterprise Security Architecture (CS502C)

15 Credit Points

A major contributing factor to cyber risk is the lack of well-designed cybersecurity architecture that protects against ever-evolving cyber-attacks. A well-designed architecture provides a streamlined workflow for security and non-security practitioners, along with increasing the robustness of an organisation’s cybersecurity. In this course you will gain the advance knowledge to develop, design and analyse security solution architectures to meet your organisation's cybersecurity objectives.

Detailed course information

Evaluation of AI Systems (CS5063)

15 Credit Points

One of the biggest challenges in Artificial Intelligence is evaluating how well AI systems work. This course will provide students of our MSc in AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies; we will also look at software testing of AI systems.

Detailed course information

Applied Artificial Intelligence (CS5079)

15 Credit Points

This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments.

Detailed course information