Program Overview

Computer Science or Computer Science (Artificial Intelligence) (2-year) MSc

Overview

This two-year master's provides a more in-depth study of taught modules with a research project that runs from September to May of the final year.

Course Details

• Duration: 2 years
• Full-time: 21 months
• Part-time: Not available
• Start date: September 2025
• UK fees: £8,967
• International fees: £21,600
• Entry requirements: 2:1 in a STEM or numerate discipline

Course Overview

This course is available to students with or without a first degree in computer science. Developments in artificial intelligence, apps, and cybersecurity are changing how we live, work, and socialize. This two-year master's provides a more in-depth study of taught modules with a research project that runs from September to May of the final year.

Taught modules in your first year will develop your knowledge in key topics such as user experience design, artificial intelligence, and data analysis. Optional modules allow you to study specialist areas, including machine learning, cybersecurity, and autonomous robotics.

In your second-year research project, you will get the opportunity to work with expert advisors on a research project.

Why Choose This Course?

• Ranked 6th in the UK for universities targeted by the largest number of top employers in the High Fliers Report The Graduate Market.
• 96.4% of postgraduates from the School of Computer Science secured work or further study within six months of graduation (HESA Graduate Outcomes 2020, using methodology set by The Guardian).
• Conversion option: No computer programming experience is needed.
• 98% of our research is classed as ‘world-leading’ (4) or ‘internationally excellent’ (3) (Research Excellence Framework 2021).

Course Content

You will study a total of 120 credits of taught modules in the first year. Your second year consists of a 60-credit enhanced research project and a 60-credit enhanced dissertation.

The Artificial Intelligence (AI) pathway allows you to graduate with a degree titled 'MSc Computer Science (Artificial Intelligence)'. You will study 40 credits of compulsory AI modules and undertake an AI-focused research project.

Core Modules

• Research Methods (20 credits): This module will expose you to a variety of research methods, providing you with good quantitative and qualitative skills.
• Programming (20 credits): This module will give you a comprehensive overview of the principles of programming, including procedural logic, variables, flow control, input and output, and the analysis and design of programs.
• Systems and Networks (20 credits): This module is part of the operating systems and networks theme. The module gives an introduction to the role of the operating system and how it manages computer resources such as memory, processes, and disks.
• Databases, Interfaces, and Software Design Principles (20 credits): This module considers both the structure of databases, including how to make them fast, efficient, and reliable, and the appropriate user interfaces which will make them easy to interact with for users.

Optional Modules

• Data Science with Machine Learning (20 credits): This module explores the range of data analysis problems that can be modeled computationally and a range of techniques that are suitable to analyze and solve those problems.
• Mixed Reality (20 credits): This module focuses on the possibilities and challenges of interaction beyond the desktop.
• Advanced Algorithms and Data Structures (10 credits): You'll study the theory used in the design and analysis of advanced algorithms and data structures.
• Advanced Computer Networks (20 credits): This module will provide you with an advanced knowledge of computer communications networks, using examples from all-IP core telecommunications networks to illustrate aspects of transmission coding, error control, media access, internet protocols, routing, presentation coding, services, and security.
• Autonomous Robotic Systems (20 credits): This module introduces the main concepts of autonomous mobile robotics, providing an understanding of the hardware and software principles appropriate for control, spatial localization, and navigation.
• Project in Advanced Algorithms and Data Structures (10 credits): This project involves a self-guided study of a selected advanced algorithm or data structure.
• Linear and Discrete Optimization (20 credits): The module provides an entry point to computational optimization techniques, particularly for modeling and solving linear and discrete optimization problems.
• Simulation and Optimization for Decision Support (20 credits): This module offers insight into the applications of selected methods of decision support.
• Games (20 credits): This module covers the history, development, and state-of-the-art in computer games and technological entertainment.
• Handling Uncertainty with Fuzzy Sets and Fuzzy Systems (20 credits): This module focuses on handling uncertainty such as vagueness using fuzzy sets and similar approaches.
• Malware Analysis (10 credits): This module looks at the practice of malware analysis, looking at how to analyze malicious software to understand how it works, how to identify it, and how to defeat or eliminate it.
• Big Data Learning and Technologies (20 credits): This module will cover four main concepts, including an introduction to big data, SQL databases vs. NoSQL databases, big data frameworks, and data mining and machine learning.
• Designing Intelligent Agents (20 credits): You’ll be given a basic introduction to the analysis and design of intelligent agents, software systems which perceive their environment and act in that environment in pursuit of their goals.
• Computer Vision (20 credits): You will examine current techniques for the extraction of useful information about a physical situation from individual and sets of images.
• Machine Learning (20 credits): Providing an introduction to machine learning, pattern recognition, and data mining techniques, this module will enable you to consider both systems which are able to develop their own rules from trial-and-error experience to solve problems as well as systems that find patterns in data without any supervision.
• Programs, Proofs, and Types (20 credits): This module focuses on some of the fundamental mathematical concepts that underlie modern programming and programming languages emphasizing the role of types.
• Software Engineering Management (20 credits): This module is part of the software engineering theme.
• Topical Trends in Cyber Security (10 credits): This module involves discussing current topics relating to computer security.
• Designing Sensor-Based Systems (20 credits): You will gain knowledge and hands-on experience of design and technical development of sensor-based systems.

Learning and Assessment

• How you will learn: Lectures, tutorials, seminars, computer labs, practical classes, project work, supervision.
• How you will be assessed: Coursework, written exam, project work.
• Contact time and study hours: The class size depends on the module. In 2021/2022, class and lecture sizes ranged from 25 to 285 students.

Entry Requirements

• Home/UK students: 2:1 (or international equivalent) in a STEM or numerate discipline.
• EU/International students: 2:1 (or international equivalent) in a STEM or numerate discipline.
• Alternative qualifications: We recognize that applicants have a variety of experiences and follow different pathways to postgraduate study.
• English language requirements: IELTS 6.5 with at least 6.0 in each element.

Fees

• Qualification: MSc
• Home/UK: £8,967
• International: £21,600 (The fee is for year one of the course; the fee for year two will be 50% of the year one fee applicable in the year that year two is taken)

Careers

• Careers advice: We offer individual careers support for all postgraduate students.
• Job prospects: This course prepares you for careers in advanced software development, particularly where reliability and efficiency are vital requirements.
• Graduate destinations: 100% of postgraduate taught students from the School of Computer Science secured graduate-level employment or further graduate study within 15 months of graduation (HESA Graduate Outcomes 2019/20 data published in 2022).