Data Analytics MSc

Select the year

2025-26

2026-27

2027-28

Start Dates

22 September 2025, 12 January 2026, 18 May 2026

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

Does working with big data excite you? Then you’ll be glad to know that the MSc in Data Analytics at The University of Huddersfield combines practical work with experiential learning to get you ready for a satisfying career in data science.

This Master’s course is designed to meet the industry demand for experts with advanced skills and knowledge in the following:

Statistics
Data mining techniques
Big data and associated file systems
Complex data visualisation.

You’ll finish our Data Analytics course with a deeper understanding of how to analyse and visualise complex datasets, evaluate existing and emerging data science technology and provide novel data solutions to stakeholders to improve their decision-making process.

Why study Data Analytics at Huddersfield?

Our hands-on Data Analytics MSc is designed to meet the demand for a new kind of IT specialist with skills and knowledge in data science. The course provides students the opportunity for professional development and valuable practice.

Our course is aligned with SAS. The SAS Institute is a multinational enterprise providing analytical solutions, platform and software, and training courses to high profile companies, and to academia. You will follow SAS training as part of your course, which puts you on the path to apply for SAS Certification and also allows you to obtain SAS Digital Badges that you can use in your CV or your online profiles to prove your skills to employers. Our partnership with SAS also gives you access to relevant job opportunities through portals like Handshake UK.

This course is also fully accredited by the British Computer Society (BCS), the Chartered Institute for IT, and by completing it, you will have partially fulfilled the academic requirements for registration as a Chartered Engineer and IT Professional.

The University is nestled within the heart of Huddersfield, a warm and welcoming town, known for its friendly atmosphere and diverse community. When you’re not studying, you can enjoy an array of exciting activities and experiences. From cultural events and charming cafes to stunning scenery and fantastic transport links, there’s plenty to do in and around the town centre.

We also offer this course as a part-time Distance Learning route.

Career opportunities after the course *

Data Scientist

Data Engineer

Data Analyst

Machine Learning Engineer

Software Engineer

*Lightcast

Who can apply?

Entry Requirements

Entry requirements for this course are normally:

A BSc, BEng or BA Honours degree (2:2 or above) or equivalent professional qualification in any subject.
Applicants with other appropriate professional qualifications and/or experience will be considered on an individual basis.

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

This module aims to provide you with skills that are key to helping you become a successful computing researcher or practitioner. You'll get the opportunity to study topics including the nature of research, the scientific method, research methods, literature review and referencing. The module aims to cover the structure of research papers and project reports, reviewing research papers, ethical issues (including plagiarism), defining projects, project management, writing project reports and making presentations.

Statistical methodology and statistical practice are very central for data analysis. Statistical methods and statistical implementation are also complementary to machine learning and data mining, covering supervised and unsupervised methods. In this module you will be exposed to current core research topics in data mining, machine learning, and interdisciplinary research in which data analysis plays an essential role. You will explore real world applications in business, e.g. customer analytics, credit scoring, financial forecasting), in health and medical research (e.g. automatic diagnosing, genetic data mining and bioinformatics), and in structured and unstructured data analysis.

Data mining is a collection of tools, methods and statistical techniques for exploring and extracting meaningful information from large data sets. It is a rapidly growing field due to the increasing quantity of data gathered by organisations. There is a potential high value in discovering the patterns contained within such data collections. In this module you will look at different data mining techniques and use appropriate data-mining tools in order to evaluate the quality of the discovered knowledge. You will study approaches to preparing data for exploration, supervised and un-supervised approaches to data mining, exploring unstructured data and the social impact of data mining. You will be expected to develop your knowledge such that you are able to contribute to discussions around current application areas and research topics and to increase your background knowledge and understanding of issues and developments associated with data mining.

The ever-increasing advancements in sensing technologies, network infrastructure, storage and social media have enabled us to acquire an unprecedented volume of data at an explosive rate. As a result, the ability to efficiently and accurately derive human-understandable knowledge from these datasets has become increasingly critical to our digitally driven society and economy. Under this Big Data phenomenon, tremendous endeavours have been devoted to tackle its underlying challenges through both novel solutions and the evolution of existing methodology. The module aims to provide you with the knowledge and critical understanding of contemporary challenges posed by the big data. The topics covered here include the fundamental characteristics and operations associated with big data; existing and emerging architectures and processing techniques; domain applications of big data in practice. Through this module, you will develop an informed understanding of the principles and practice of big data analytics in both general and application specific contexts.

Machine Learning techniques are now used widely in a range of applications either stand-alone or integrated with other AI techniques. The Machine Learning module allows you to obtain a fundamental understanding of the subject as a whole: how to embody machines with the ability to learn how to recognise, classify, decide, plan, revise, optimise etc. You will learn which machine learning techniques are appropriate for which learning problem, and what the advantages and disadvantages are for a range of ML techniques. We will consider the widely known data-driven approaches, and specific techniques such as “deep learning”, and investigate the typical applications and potential limitations of these approaches. We will introduce available tools and use them in practical classes, evaluating learning bias and characteristics of training sets. High profile applications of data driven, stand-alone, ML systems will be investigated, such as the AlphaGo method. Where data is sparse, and knowledge is already present in a system, we will investigate methods to improve heuristics of existing AI systems, and to learn or revise domain knowledge. This is essentially the area of model-driven ML, where is often integrated to other reasoning systems.

The purpose of this module is to enable you to appreciate the historical, current and future application areas of Artificial Intelligence and Data Analytics in relation to both theoretical and practical aspects and to investigate at least one application area in depth. Case studies discussed in the sessions will provide an exploration of applications in a variety of different areas and will be achieved by combinations of study of current research papers, tutors’ own research & the investigative work of the students within the module.

With ever-increasing advancements in Internet-of-Things, Cyber-Physical Systems, and social media applications, huge volumes of complex and multi-dimensional datasets are being generated every day. Visually analysing these datasets facilitates the transformation of raw data into valuable knowledge and information. The biggest challenge is to articulate suitable solutions of complex analytical problems by visually interacting with the designed artefacts without going into underlying complexities. Tremendous endeavours have been devoted to streamline innovative solutions, novel methods, tools, processes and methodologies to address underlying challenges. This module aims to provide you with core knowledge and deep understanding of advanced theories underpinning data visualisation, best practices in using visualisation artefacts effectively and practical skills in implementing the theoretical knowledge into certain application domains. You will be engaged in practical utilisation of state-of-the-art visualisation tools and methods to understand real-world big data problems, and to rectify complex issues with visual analysis. Topics that will be covered in this module include exploratory data visualisation; data visualisation theories, existing and emerging interactive 2D and 3D visualisation toolkits, and application of visualisation skillset in application specific domains.

The data needs of modern enterprises and organisations require a more flexible approach to data management than that offered by traditional relational database management systems. With organizations increasingly looking to Big Data to provide valuable business insights, it has become clear that new approaches are required to handle these new data requirements. Primarily focusing on non-relational data models, this module introduces you to alternative approaches to modelling the data needs of an organization. It also provides you with an opportunity to use non-relational databases and database technologies to build robust and effective organizational information systems.

This module enables you to work independently on a project related to a self-selected problem. A key feature in this final stage of the course is that you will be encouraged to undertake an in-company project with an external Client. Where appropriate, however, the Project may be undertaken with an internal Client - research-active staff - on larger research and knowledge transfer projects. The Project is intended to be integrative, a culmination of knowledge, skills, competencies and experiences acquired in other modules, coupled with further development of these assets. In the case where an external client is involved, both the Client and Student will be required to sign a learning agreement that clearly outlines scope, responsibilities and ownership of the project and its products or other deliverables. The Project will be student-driven, with the clear onus on you to negotiate agreement, and communicate effectively, with all parties involved at each stage of the Project.

Teaching and Assessment

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

Where could this lead you?

Your Career

The top five job titles advertised in the UK for graduate roles associated with Data Analytics MSc courses are: Data Scientist; Data Engineer; Data Analyst; Machine Learning Engineer; and Software Engineer.

Source: LightcastTM data - job postings from December 2023 to December 2024 showing jobs advertised associated with a selection of relevant graduate roles.

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.

£38.5k
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.

The learning environment provided me with cutting-edge skills and the confidence to succeed in a competitive job market. After completing my MSc, I secured a role as a Senior Analyst with E.ON UK Plc. My time at Huddersfield was transformative, setting me on a path to a fulfilling career.

- Lucia Nnami
Data Analytics MSc Graduate

How much will it cost?

Fees and Finance

£9,900 per year

This information is for Home students applying to study at the University of Huddersfield in the academic year 2025/26.

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/

This information is for international students applying to study at the University of Huddersfield in the academic year 2025/26.

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 univsersity 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 the University of Huddersfield

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Watch our on-demand webinar

Join Dr Shamaila Iram, Senior Lecturer and Course Leader, to explore our online Data Analytics MSc and dive into the course content and key benefits.

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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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Careers support

We know you’re coming to university to study on your chosen subject, meet new people and broaden your horizons. However, we also help you to focus on life after you have graduated to ensure that your hard work pays off and you achieve your ambition.

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Student support

At the University of Huddersfield, you’ll find support networks and services to help you get ahead in your studies and social life. Whether you study at undergraduate or postgraduate level, you’ll soon discover that you’re never far away from our dedicated staff and resources to help you to navigate through your personal student journey.

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Teaching Excellence

Great teaching is engaging and inspiring — it helps you reach your full potential and prepares you for the future. We don’t just teach well — we excel — and we have the awards and recognition to prove it.

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Inspiring Academics

Our researchers carry out world-leading work that makes a real difference to people’s lives. Staff within the Department of Computer Science may teach you on this course.

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Research Excellence

You’ll be taught by staff who want to support your learning and share the latest knowledge and research.

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Accommodation

Looking for student accommodation? Huddersfield has you covered. HudLets has a variety of accommodation types to choose from, no matter what your preference. HudLets is the University’s approved accommodation service, run by Huddersfield Students’ Union.

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Further Study

Many of our graduates stay at Huddersfield to complete postgraduate research degrees at Masters or PhD level.

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Legal information

When you enrol as a student of the University, your study and time with us will be governed by our terms and conditions, Handbook of Regulations and associated policies. It is important that you familiarise yourself with these as you will be asked to agree to them when you join us as a student. You will find a guide to the key terms here, along with the Student Protection Plan.

Although we always try and ensure we deliver our courses as described, sometimes we may have to make changes for the following reasons:

Changes to a course you have applied for but are not yet enrolled on

If we propose to make a major change to a course that you are holding an offer for, then we will tell you as soon as possible so that you can decide whether to withdraw your application prior to enrolment. We may occasionally have to withdraw a course you have applied for or combine your programme with another programme if we consider this reasonably necessary to ensure a good student experience, for example if there are not enough applicants. Where this is the case we will notify you as soon as reasonably possible and if you are unhappy with the change we will discuss with you other suitable courses we can transfer your application to. If you do not wish to transfer to another course with us, you may cancel your application and we will refund you any deposits or fees you have paid to us.

Changes to your course after you enrol as a student

Changes to option modules

Where your course allows you to choose modules from a range of options, we will review these each year and change them to reflect the expertise of our staff, current trends in research and as a result of student feedback or demand for certain modules. We will always ensure that you have an equivalent range of options to that advertised for the course. We will let you know in good time the options available for you to choose for the following year.

Major changes

We will only make major changes to non-optional modules on a course if it is necessary for us to do so and provided such changes are reasonable. A major change is a change that substantially changes the outcomes, or a significant part of your course, such as the nature of the award or a substantial change to module content, teaching days (part time provision), type of delivery or assessment of the core curriculum. For example, it may be necessary to make a major change to reflect changes in the law or the requirements of the University’s regulators or a commissioning or accrediting body. We may also make changes to improve the course in response to student, examiners’ or other course evaluators’ feedback or to ensure you are being taught current best practice. Major changes may also be necessary because of circumstances outside our reasonable control, such as a key member of staff being unable to teach due to illness, where they have a particular specialism that can’t be adequately covered by other members of staff; or due to pandemics, other disasters (such as fire, flood or war) or changes made by the government.

Major changes would usually be made with effect from the next academic year, but may happen sooner in an emergency. We will notify you as soon as possible should we need to make a major change and will consult with affected groups of students and any changes would only be made in accordance with our regulations. If you reasonably believe that the proposed change will cause you detriment or hardship we will, if appropriate, work with you to try to reduce the adverse effect on you or find an appropriate solution. Where an appropriate solution cannot be found and you let us know before the change takes effect you can cancel your registration and withdraw from the University without liability to the University for any additional tuition fees. We will provide reasonable support to assist you with transferring to another university if you wish to do so and you may be eligible for an exit award depending on how far through your course you are.

In exceptional circumstances, we may, for reasons outside of our control, be forced to discontinue or suspend your course. Where this is the case, a formal exit strategy will be followed in accordance with the student protection plan.

The Office for Students (OfS) is the principal regulator for the University.

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Data Analytics MSc

Overview

Why choose Huddersfield for this course?

Accreditation and Professional Links

Entry Requirements