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Computer Science MSc (Distance Learning)

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Start Dates

6 September 2027, 17 January 2028, 8 May 2028

Duration

2-3 years part-time


Recent Awards For Excellence

Computer Science & Information Systems - QS 2025
Find out more about these awards
About this course

Overview

Why choose Huddersfield for this course?

  • Gain advanced skills and knowledge across AI, Cyber Security and Data Science, the core domains, shaping today’s digital world.
  • Develop practical, industry-relevant expertise in designing, building and evaluating modern computing systems.
  • Flexible, part-time 100% online study, designed for working professionals.

Accreditation and Professional Links

Recognised connections to give you an extra edge when you graduate. Read More

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 100% online, flexible part-time 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 full-time, on-campus.

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 with a minimum score of 6.0 in writing and a minimum of 5.5 in any single component or Duolingo English certificate, score 105 or above. 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.

Secure System Design is a practical, design led 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, human centred 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 third party dependencies. The module places emphasis on clear risk communication, defensible trade offs between security and usability, and evidence based design rationales. By the end, you will be equipped to plan, design and justify an end to end secure software solution, and explain its security properties to both technical and non technical 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.

This module enables you to independently undertake a project based on a problem of your own choosing. Designed to be integrative, the project serves as a culmination of the knowledge, skills, competencies and experiences you've gained throughout your studies, while also encouraging further development in these areas. As the project is student-led, you will take ownership of the project from start to finish — negotiating agreements, managing communications, and collaborating effectively with all stakeholders at each stage. In addition, the module offers a comprehensive overview of the research process, academic writing, and key professional considerations including legal, ethical and social issues. It also supports your career development by exploring employability pathways and professional growth.

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. The module emphasises extracting actionable insights in data science challenges. 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.

You will also choose 1 optional module in the year. The current option modules are:

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 introduces you to the essential principles and practices of cyber security. You’ll explore topics such as digital threats, malware, cryptography, network and software security, and the human and legal aspects of protecting systems. Through a mix of lectures, interactive sessions, and hands-on labs, you’ll learn how cyber attacks happen and how to defend against them using real-world tools and techniques. You’ll also examine the role of governance, privacy rights, and emerging technologies like AI and IoT in shaping the future of cyber security. By the end of the module, you’ll be equipped with the knowledge and practical skills to critically assess security risks and contribute to safeguarding digital environments.

For more information on when and how we update our modules please see the ‘Legal Information’ section below.

Teaching and Assessment

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

Technology and System Requirements

As a Distance Learning student, you must provide and have access to certain IT equipment and facilities to access your Virtual Learning Environment (VLE) and to fully participate on your course.

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% 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

£9,900

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

Modules credits can range from 15 to 60, dependent on the content of the module. Read more about total credits required for a range of degrees, to allow you to calculate the potential total cost.

Please note that tuition fees for subsequent years may rise in line with inflation (RPI-X) and/or Government policy and/or to ensure our distance learning fees are competitive.

Tuition fees will cover the cost of your study at the University. Read more about what is and is not covered by Tuition Fees including compliance for Goods and Services Tax for International Students studying an online course. 

For detailed information please visit www.hud.ac.uk/distance-learning/fees-and-finance/ 

£9,900

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

Modules credits can range from 15 to 60, dependent on the content of the module. Read more about total credits required for a range of degrees, to allow you to calculate the potential total cost.

Please note that tuition fees for subsequent years may rise in line with inflation (RPI-X) and/or Government policy and/or to ensure our distance learning fees are competitive.

Tuition fees will cover the cost of your study at the University. Read more about what is and is not covered by Tuition Fees including compliance for Goods and Services Tax for International Students studying an online course. 

For detailed information please visit www.hud.ac.uk/distance-learning/fees-and-finance/

Flexible payments

Learn how to pay your fees including flexible instalment options

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Funding options

Explore ways to fund your course with exclusive discounts and government loans

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

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Why Hud

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