Computer Science MSc

Select the year

2026-27

2027-28

Start Dates

20 September 2027, 10 January 2028

Duration

1 year full-time

Recent Awards For Excellence

Computer Science & Information Systems - QS 2025

Find out more about these awards

About this course

Overview

From the software we use every day to the systems that support global digital infrastructure, computer science sits at the heart of modern technology. Our Computer Science MSc enables you to deepen your understanding of advanced computing while developing the skills needed to design and build reliable, high-performance systems.

On this course, you will explore both the theoretical foundations and practical techniques that underpin contemporary computer science. You will study topics such as software engineering, advanced data mining, applied artificial intelligence, machine learning and secure system design, developing the ability to select and apply appropriate computational methods to solve complex problems.

Alongside technical knowledge, the course emphasises the design, implementation and evaluation of high-quality computing solutions using modern tools, programming languages, frameworks and development practices. You will also consider important professional issues such as security, ethics and the wider social impact of digital technologies.

A substantial individual project forms a key part of the MSc, allowing you to apply your knowledge to a realistic computing challenge aligned with your interests or career ambitions. This prepares you for roles in areas such as software engineering, data and AI-enabled systems, cyber security, or for further research-focused study.

This course is also offered part-time, distance learning. Find out more about Distance Learning at Huddersfield.

Career opportunities after the course *

Software Engineer

Data Engineer

Data Analyst

Solutions Architect

Systems Engineer

*Lightcast

Who can apply?

Entry Requirements

Entry requirements for this course are normally:

A BSc or BEng Honours degree (2:2 or above) in Computing or related subject or an equivalent professional qualification. For applicants who received their degree more than 10 years ago, we will need evidence to demonstrate current knowledge in the subject area, such as reference letters, training certificates or significant relevant work experience.
Other qualifications and/or experience that demonstrate appropriate knowledge and skills at an Honours degree level.

If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum for IELTS is 6.0 overall with no element lower than 5.5, or equivalent. Read more about the University’s entry requirements for students outside of the UK on our International Entry Requirements page.

What will you learn?

Course Details

Machine Learning (ML) techniques power many of today’s most transformative technologies, from intelligent assistants and recommender systems to autonomous vehicles and medical diagnostics. This module will introduce you to the key principles and algorithms of ML, both as independent systems and as integral components within broader AI frameworks. You will develop a strong conceptual and practical understanding of how machines can learn from data and experience to recognise patterns, classify information, make predictions, and optimise decisions. You will also explore how to select suitable learning methods for different problem types, analysing the strengths, limitations, and trade-offs between classical and modern approaches. Topics include data-driven learning methods such as tree-based models, ensemble learning, kernel methods, clustering techniques, artificial neural networks and their real-world applications. Through hands-on practical sessions, you will work with widely adopted machine learning tools and frameworks to develop a practical understanding of how core algorithms operate in practice, including data preparation, model training, performance evaluation, and bias analysis.

In this module, you will explore how Artificial Intelligence (AI) is applied across real-world domains to solve complex problems and drive innovation. You will study key areas such as computer vision, natural language processing, large language models, chatbots, autonomous systems, and intelligent decision-making. You will learn how AI technologies are integrated into systems used in industry, public services, and research, while considering their capabilities, limitations, explainability, robustness, and ethical implications. Through practical examples and case studies, you will discover how AI is shaping sectors including healthcare, finance, transport, supply chains, and the creative industries. By the end of this module, you will understand how to connect theoretical concepts of AI with their real-world applications and appreciate the impact of AI on society and the future world of work.

Data Mining involves using tools, methods, and statistical techniques to extract valuable insights from large datasets. As data volume grows, the potential to uncover meaningful patterns increases. In this module, you'll explore various data mining techniques and tools, focusing on data preparation, exploration, types, modelling, pattern mining, and the social impact of data mining. Essentially, this module emphasises the exploratory and interpretative analysis of complex, real-world datasets, using overlapping techniques for fundamentally different analytical purposes such as pattern discovery, insight generation, and decision support. You'll be expected to develop a deep understanding of real-world applications and research areas, enhancing your ability to contribute to discussions on data mining issues and advancements.

Secure System Design is a practical, designled module focused on building software that is secure by default. You will develop a critical grasp of the principles, patterns and processes that underpin secure systems, including security requirements, secure DevOps practices, security architecture patterns, Zero Trust principles, privacy by design, humancentred security, secure APIs and interfaces, supply chain security considerations, and formal reasoning concepts for validating security properties. You will apply these in realistic design scenarios: eliciting and prioritising requirements, integrating security into development workflows, selecting and justifying architectural and interface patterns, and addressing systemic risks such as thirdparty dependencies. The module places emphasis on clear risk communication, defensible tradeoffs between security and usability, and evidencebased design rationales. By the end, you will be equipped to plan, design and justify an endtoend secure software solution, and explain its security properties to both technical and nontechnical stakeholders.

This module will focus on examining algorithm development and software engineering. You will study programming fundamentals, object-oriented programming and genericity. You will consider algorithms, data structures and programming paradigms that enable efficient implementation, while covering persistence and concurrency. You will analyse issues associated with software engineering project development and examine practices, procedures, techniques and tools designed to address these issues. You will also explore the advent of modern AI-assisted coding paradigms. In covering these topics, the module will examine the issues that software programmers and developers face every day in their quest to develop successful technology systems and applications.

In this module, you will learn how to design and build scalable data systems that can handle real-world, large-scale datasets. You will explore how big data analytics and modern database technologies work together, compare different data models and architectures, and apply advanced techniques for query processing and optimisation. You will also gain practical experience in creating data pipelines that integrate machine learning, data visualisation, and domain-specific analytics.

This module explores how statistical methods and predictive models drive intelligent, data-driven decision-making. You will develop a practical understanding of statistical reasoning, hypothesis testing, and uncertainty analysis, and learn how these foundations support real-world data science and AI applications. You will examine how traditional statistical approaches connect with modern predictive analytics, combining techniques from machine learning and data mining to interpret and forecast outcomes from complex datasets. Using industry-standard tools such as SAS, you will gain experience in building and evaluating predictive models across different domains, including business, healthcare, and finance. Case studies and applied projects will help you apply your skills to real data and understand how statistical thinking underpins advanced AI-enabled decision systems.

This module provides a theoretical and practical foundation for leveraging artificial intelligence to advance modern cyber security. You will begin by exploring how AI theory can be applied to identify and predict emerging threats, understand adversarial behaviour, and detect deeply hidden malicious patterns that evade traditional defence systems. From there, you will transition to the practical applications of AI in securing digital assets. You will learn how to implement AI-driven solutions for next-level biometric and access control, advanced loss prevention, and the use of anonymization and encryption techniques to protect sensitive data. Through this module, you will gain the skills to move from a reactive security posture to a proactive and intelligent one, using the power of AI to build more resilient and sophisticated cyber defences.

Teaching and Assessment

Discover what to expect from your tutor contact time, assessment methods, and feedback process.

Where could this lead you?

Your Career

Graduates of the Computer Science MSc can progress into a wide range of technical and analytical roles across industries including technology, finance, healthcare, and the public sector. Many pursue careers as Software Engineers, Data Engineers, Systems Engineers or DevOps Engineers, designing and maintaining digital systems and infrastructure. Opportunities also include specialist roles such as Data Analyst, Data Scientist, Security Engineer and Solutions Architect, applying expertise to solve complex challenges and support organisational innovation. These skills are highly sought after by tech companies, consultancies, start-ups and large multinational organisations.

Source: Lightcast data extracted from the Graduate Career Explorer

98% Percentage of the University's postgraduate students go on to work and/or further study within fifteen months of graduating.

* HESA Graduate Outcomes 2022/23, UK domiciled.

£38,500 The average salary of our postgraduates fifteen months after graduating.

* HESA Graduate Outcomes 2022/23, mean salary, UK domiciled, full-time UK employment as main activity.

"My degree hugely lifted my knowledge and provided me so much knowledge within this industry. My experience, with my BSc and Master's degree helped me to get my current job on software development."

- Henry Chung
Computing MSc Graduate

How much will it cost?

Fees and Finance

£8,225 per year

This is the tuition fee for 2026/27 entry. Tuition fees for 2027/28 will be published once the information becomes available.

This information is for Home students applying to study at the University of Huddersfield in the academic year 2026/27.

Please note that tuition fees for subsequent years may rise in line with inflation (RPI-X) and/or Government policy.

For detailed information please visit https://www.hud.ac.uk/study/fees/

£18,700 per year

This is the tuition fee for 2026/27 entry. Tuition fees for 2027/28 will be published once the information becomes available.

This information is for international students applying to study at the University of Huddersfield in the academic year 2026/27.

Please note that tuition fees for subsequent years may rise in line with inflation (RPI-X) and/or Government policy.

For detailed information please visit https://www.hud.ac.uk/international/fees-and-funding/

Scholarships and Bursaries

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What’s included in your fee?

We want you to understand exactly what your fees will cover and what additional costs you may need to budget for when you decide to become a student with us.

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If you have any questions about Fees and Finance, please email the Student Finance Team.

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What does the University offer?

Gallery

See below for a glimpse at some of our facilities

The Spärck Jones Building

The Study Mill

A wide range of computing labs

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Computer Science at Huddersfield

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Department of Computer Science Tour

Join Isobel, a current Computer Science student, for a tour of our computing facilities

Our research centres

The Department of Computer Science is home to a number of world-class research centres and institues, each exploring global grand challenges in areas such as transport, health, security and energy.

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Why Hud

Explore the unique opportunities and resources that make our institution a top choice for students seeking a well-rounded and future-focused education.

Explore Huddersfield

Make Huddersfield your home. A Yorkshire town, surrounded by beautiful countryside, with easy access to neighbouring cities; Leeds, Manchester and Sheffield. You’ll find plenty of places to eat, drink, shop and socialise, there’s ambitious plans for future development. Our campus is situated next to the town centre - making your commute a breeze.

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Your Student Experience

Get involved in great opportunities helping you to make friends from all across the world and create lifelong memories. Join one of over 100 societies with the Students’ Union, experience new cultures through global events, earn whilst you learn and build your skills via our Global Professional Award.

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Budget Friendly

Huddersfield is not only one of the friendliest towns, it also offers you a lower cost of living than most big cities. This means you could have more money to spend, making your uni experience even better. On campus you’ll also find plenty of facilities and services to help you budget and make your money go further.

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Sustainability Matters

We’re committed to sustainability and aim to be carbon neutral by 2030. Our plan includes reducing emissions, enhancing biodiversity, and improving wellbeing through sustainable buildings. We’re investing in digital solutions, low-impact travel, and embedding sustainability into teaching and research, investing over £1m in carbon reduction.

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Committed to Your Future

Since 2015, we’ve invested £198 million to create spaces where you can learn, collaborate and thrive. We’re continuously investing in our campus with your wellbeing in mind—adding features that make our buildings healthier, more supportive and better places for you to succeed.

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Computer Science MSc

Overview

Why choose Huddersfield for this course?

Accreditation and Professional Links

Entry Requirements