Key information
Accreditation:
This course is Accredited
Typical offer:
A second-class honours degree in a relevant subject, or equivalent professional experience and/or qualifications
Showing content for section Overview
Overview
Master big data methodologies and find the valuable trends and patterns buried in complex datasets using machine learning. On our MSc Data Analytics course, you'll learn how to use data mining tools, machine learning methods and big data concepts as you unlock specialist knowledge of professional analysis methods.
You'll apply your theoretical learning to handling real data, analysing large data sets drawn from professional partners, such as IBM, or from live University research into cosmology, health informatics and cybersecurity and robotics.
You'll plan, design and produce an in-depth research project, using analytics packages like Hadoop, Python, KNIME, PostgreSQL and Tableau. We'll provide the expertise and support so you can develop your dissertation and shape your professional practice. And once you graduate, you'll have a skillset that'll get you noticed – and all the tools you need to progress your career in data analytics or deep learning.
The СÀ¶ÊÓƵ is ranked 5th of the modern universities for research quality in computer science and informatics
Research Excellence Framework (REF) 2021
Eligibility
This course accepts UK, EU, and International students.
Course highlights
- Plan and deliver your Master's project in collaboration with an industry partner – previous projects have analysed data from Fresh Relevance, Specsavers and IBM to support strategic priorities
- Build your own database from complicated, real-world datasets, and apply robust statistical methods to produce actionable, data-driven insights
- Use industry-standard software, such as Knime, Tableau, Hadoop and Spark, and engage with modern techniques including machine learning, AI, and Business Intelligence Modeling
- Convert your existing study or workplace knowledge into a necessary skillset for modern data-driven careers
Accreditation
This course is accredited by the British Computer Society (The Chartered Institute for IT), partially meeting the educational requirement for CITP and CEng.
Contact information
Contact AdmissionsEntry requirements​
Eligibility
This course accepts UK, EU, and International students.
January 2025 start
- A second-class honours degree in a relevant subject, or equivalent professional experience and/or qualifications.
Please get in touch if you're not sure if your undergraduate subject is relevant to this degree.
Equivalent professional experience and/or qualifications will also be considered, such as previous study, employment, voluntary work and training courses, including courses and qualifications you didn't complete. Learn more about our Recognition of Prior Learning (RPL).
If you're applying as an international student with a non-UK degree, you’ll need to show you meet the UK entry requirements listed above.
To find out if your non-UK degree or other qualification is accepted, please visit our page for your country and view the UK equivalent of your qualification.
- English language proficiency at a minimum of IELTS band 6.0 with no component score below 5.5.
You do not need an IELTS or equivalent certification if:
- you have a UK degree
- you have a degree from a majority English speaking country (not taught by Distance Learning)
- you are a national of a majority English speaking country
Degrees taught solely in English from non-majority English speaking countries will be considered on a case by case basis. Find out more about our English language requirements.
If you do not meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
September 2025 / January 2026 start
- A second-class honours degree in a relevant subject, or equivalent professional experience and/or qualifications.
Please get in touch if you're not sure if your undergraduate subject is relevant to this degree.
Equivalent professional experience and/or qualifications will also be considered, such as previous study, employment, voluntary work and training courses, including courses and qualifications you didn't complete. Learn more about our Recognition of Prior Learning (RPL).
If you're applying as an international student with a non-UK degree, you’ll need to show you meet the UK entry requirements listed above.
To find out if your non-UK degree or other qualification is accepted, please visit our page for your country and view the UK equivalent of your qualification.
- English language proficiency at a minimum of IELTS band 6.0 with no component score below 5.5.
You do not need an IELTS or equivalent certification if:
- you have a UK degree
- you have a degree from a majority English speaking country (not taught by Distance Learning)
- you are a national of a majority English speaking country
Degrees taught solely in English from non-majority English speaking countries will be considered on a case by case basis. Find out more about our English language requirements.
If you do not meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
Costs and funding
Tuition fees (January 2025 start)
- Full-time: £10,400 (may be subject to annual increase)
- Part-time: £5,200 per year (may be subject to annual increase)
- Full time: £10,400 (may be subject to annual increase)
- Part-time: £5,200 per year (may be subject to annual increase)
These figures both include the Transition Scholarship for EU students.
- Full-time: £19,200 (may be subject to annual increase)
- Part-time: £9,600 per year (may be subject to annual increase)
Tuition fees (September 2025 / January 2026 start)
- Full-time: £10,900 (may be subject to annual increase)
- Part-time: £5,450 per year (may be subject to annual increase)
- Full time: £10,900 (may be subject to annual increase)
- Part-time: £5,450 per year (may be subject to annual increase)
These figures both include the Transition Scholarship for EU students.
- Full-time: £19,200 (may be subject to annual increase)
- Part-time: £9,600 per year (may be subject to annual increase)
СÀ¶ÊÓƵ graduates may receive a 20% alumni tuition fee discount.
Fees are subject to annual increase. Read our tuition fees terms and conditions.
You'll be able to pay your fees in instalments. Find out how to pay your tuition fees.
Funding your studies
Explore how to fund your studies, including available scholarships and bursaries.
If you're a UK student, you may be eligible for a Government Postgraduate Master's Loan, which you can use to help with course fees and living costs.
Loans, scholarships and bursaries
Browse funding such as the Government Postgraduate Loan, our scholarships for new and returning students, and subject specific loans.
Funding for international students
Learn more about sponsorships, scholarships and loans for students applying from outside of the UK.
Fees and funding for Master's courses
Explore Master's funding options, including loans, scholarships, bursaries and more.
Additional costs
These course-related costs aren't included in the tuition fees, so you'll need to budget for them when you plan your spending. Additional costs could include:
- Accommodation: Accommodation options and costs can be found on our accommodation pages.
- Recommended reading: You can borrow key texts from the library and if you choose to purchase these texts they may cost up to £60 each.
- General costs: Such as photocopying, memory sticks, printing charges, binding and specialist printing. We suggest budgeting £75 per year.
- Final project transport or accommodation: where necessary, which related to your research activities. The amount will depend on the project you choose.
Read more about tuition fees and living costs, including what your tuition fees cover.
Modules
Modules
Core
You'll study and build current models, such as non-relational (NoSQL) and cloud relational databases, and master the implications of ethical and professional data management codes. When you complete the module, you'll have the perspective to professionally unleash the power of your data.
Applying advanced techniques like semantic analysis and clustering algorithms, you will uncover hidden patterns across text, speech and multimedia to solve real-world challenges.
You'll use industry-standard applications and relevant programming languages, such as Python, to solve problems in data analytics, artificial intelligence and machine learning. As you analyse programming concepts and troubleshoot your own code, you'll strengthen your ability to work with and create data applications.
In this research-informed module, you'll learn to use scale-out architectures and platforms, then apply your knowledge to two complex datasets drawn from your lecturers' research interests (such as cybersecurity, healthcare, robotics or cosmology). You'll also develop the confidence to advise on the use of AI and big data for live problems.
In this module, you'll sharpen your data communication abilities by using visualisation tools and forecasting techniques to create clear dashboards, in line with best practice in the data analytics field.
Whether you're developing novel software or pursuing theoretical advances, you'll formulate robust aims backed by methodical data gathering/analysis. Once you've reached your findings, you'll present polished written and oral reports that show your knowledge of ethical and professional considerations, demonstrating your abilities to direct projects advancing industry or academia.
Optional modules
You'll use cloud-based data warehousing, multi-dimensional modelling and professional coding techniques to discover and visualise your BI insights.
On this module, you'll grasp the theories associated with information security and examine the major current threats in the field. You'll also explore core technical topics, such as access control and cryptography, alongside legal and ethical issues in hacking and information security.
You'll study the concepts that inform explainable AI (XAI), and its ability to audit processes, surface insights and quantify fairness. Then you'll design and build XAI systems able to respond to industry case studies, and validate your results. Working with innovative tools like SHAP and LIME, you'll work toward delivering AI that augments human intelligence - fostering collaboration rather than replacement as systems permeate everyday experiences.
You'll dig into algorithms, probability models and ways to perform "risky inference" as you build a data model. Using concepts such as cross validation, Bayesian inference and regularisation, you'll prepare for careers or further research in machine learning, with advanced understanding of the theories that power it.
Modules
Core
You'll study and build current models, such as non-relational (NoSQL) and cloud relational databases, and master the implications of ethical and professional data management codes. When you complete the module, you'll have the perspective to professionally unleash the power of your data.
You'll use industry-standard applications and relevant programming languages, such as Python, to solve problems in data analytics, artificial intelligence and machine learning. As you analyse programming concepts and troubleshoot your own code, you'll strengthen your ability to work with and create data applications.
In this module, you'll sharpen your data communication abilities by using visualisation tools and forecasting techniques to create clear dashboards, in line with best practice in the data analytics field.
Optional modules
You'll use cloud-based data warehousing, multi-dimensional modelling and professional coding techniques to discover and visualise your BI insights.
On this module, you'll grasp the theories associated with information security and examine the major current threats in the field. You'll also explore core technical topics, such as access control and cryptography, alongside legal and ethical issues in hacking and information security.
You'll study the concepts that inform explainable AI (XAI), and its ability to audit processes, surface insights and quantify fairness. Then you'll design and build XAI systems able to respond to industry case studies, and validate your results. Working with innovative tools like SHAP and LIME, you'll work toward delivering AI that augments human intelligence - fostering collaboration rather than replacement as systems permeate everyday experiences.
You'll dig into algorithms, probability models and ways to perform "risky inference" as you build a data model. Using concepts such as cross validation, Bayesian inference and regularisation, you'll prepare for careers or further research in machine learning, with advanced understanding of the theories that power it.
Core
Applying advanced techniques like semantic analysis and clustering algorithms, you will uncover hidden patterns across text, speech and multimedia to solve real-world challenges.
In this research-informed module, you'll learn to use scale-out architectures and platforms, then apply your knowledge to two complex datasets drawn from your lecturers' research interests (such as cybersecurity, healthcare, robotics or cosmology). You'll also develop the confidence to advise on the use of AI and big data for live problems.
Whether you're developing novel software or pursuing theoretical advances, you'll formulate robust aims backed by methodical data gathering/analysis. Once you've reached your findings, you'll present polished written and oral reports that show your knowledge of ethical and professional considerations, demonstrating your abilities to direct projects advancing industry or academia.
Changes to course content
We use the best and most current research and professional practice alongside feedback from our students to make sure course content is relevant to your future career or further studies.
Therefore, some course content may change over time to reflect changes in the discipline or industry. If a module doesn't run, we'll let you know as soon as possible and help you choose an alternative module.
I knew about mathematics, statistics and data analysis tools, but I didn’t have the skills to deal with Big Data. I looked for the right degree to get these skills and the СÀ¶ÊÓƵ was the choice that suited my aspirations and needs.
How you'll spend your time
We recognise that you'll probably be juggling more demands when you do your Master's degree, as you may be working or you may have family responsibilities.
We'll give you as much indication here as we can of how much time you'll need to be on campus and how many hours you can expect to spend in self-directed study, but please note that these indications are always subject to change. You should receive your full timetable several weeks before you start with us.
Course structure
This Master's degree will take 12 months (full-time study) or 2 years (part-time study).
You can expect:
- 8 to 12 hours of teaching per week (4 to 6 hours for part-time students). We do our best to keep all teaching within three days, leaving you the rest of the week for work experience or self-guided study
- 20 hours of independent study each week (10 hours for part time students)
In the last 3 months of the course you'll be focusing on your research project.
Teaching
Master's study is deeper and more specialised than an undergraduate degree. This means you'll focus on something that really matters to you and your career as you work closely with academics committed to the subject.
You'll spend more time in independent study and research than you did for your undergraduate degree, but the majority of your teaching time will be in-person and face-to-face.
Teaching on this course includes:
- lectures
- tutorials
- lab sessions
Assessment
You’ll be assessed primarily through coursework on this programme, but there is a small number of exams.
Term dates
September start
The Master's academic year runs from September to the following September. There are breaks at Christmas and Easter. Over the summer you'll be writing your project/dissertation.
Joining us as an international student
You'll feel at home in our international community and our diverse city. You'll be joining over 5,000 international students from more than 150 countries who are studying with us.
Learn more about international student life and how we can help you with visas, applications, arrival and settling in.
Your facilities
SCIAMA Supercomputer
Find out how the Institute of Cosmology and Gravitation's SCIAMA Supercomputer is helping answer questions about the origins of the universe, and much more.
Cisco Networking Academy
Use our bespoke network laboratory with in-lab and remote access to over 200 routers and switches in a data-centre environment. The lab also has specialist dual-boot (Linux and Windows) PCs and a private cloud, for implementing and testing virtualised computing and network infrastructures.
Career development
Careers this Master’s prepares you for
As a successful graduate of this course, you'll be able to show the enhanced skills in data science and analytics that companies need to extract the most valuable information from their data.
You'll have demonstrable experience with industry-standard software, and, if you choose to work with live company data in your studies, you'll have made professional contacts in the industry while making your analytical insights.
You'll also be an expert in new techniques and technologies in the field, with an eye for future developments, making you highly employable.
Graduates of this course have gone onto roles such as:
- Senior data scientist
- Data architect
- Data officer
- Information strategist
- PhD research
Career outcomes shown are sourced from the latest available graduate outcome surveys. The data shows career outcomes at 15 months after graduation.
Career planning
During your course you'll have expert careers advice from our Careers and Employability Centre, your tutors and our Student Placements and Employability Centre. You can access support from our Careers and Employability Centre for up to 5 years after you graduate.
Career support
You'll benefit from:
- Networking events
- 1-to-1 appointments
- CV and cover letter advice
- Interview preparation and practice
- Workshops to enhance your employability skills
- Recruitment events, including the Student and Graduate Opportunities Fair
- Support starting your own business
Supporting you
Master's study is more focused on independent learning than undergraduate study, but you'll get lots of support via video, phone and face-to-face from teaching and support staff to enhance your learning experience and help you succeed. You can build your personalised network of support from the following people and services:
Types of support
Your personal tutor helps you make the transition to postgraduate study and gives you academic and personal support throughout your Master's.
As well as regular scheduled meetings with your personal tutor, they're also available at set times during the week if you want to chat with them about anything that can't wait until your next meeting.
You'll have help from a team of faculty learning support tutors. They can help you improve and develop your academic skills and support you in any area of your study in one-on-one and group sessions.
They can help you:
- master the mathematics skills you need to excel on your course
- understand engineering principles and how to apply them in any engineering discipline
- solve computing problems relevant to your course
- develop your knowledge of computer programming concepts and methods relevant to your course
- understand and use assignment feedback
All our labs and practical spaces are staffed by qualified laboratory support staff. They’ll support you in scheduled lab sessions and can give you one-to-one help when you do practical research projects.
During term time, Faculty Academic Skills Tutors (AST) are available for bookable 1-to-1 sessions, small group sessions and online sessions. These sessions are tailored to your needs.
Support is available for skills including:
- University study
- Getting into the right study mindset
- Note-taking and note-making skills
- Referencing
- Presentation skills
- Time management, planning, and goal setting
- Critical thinking
- Avoiding plagiarism
If you have a disability or need extra support, the Additional Support and Disability Centre (ASDAC) will give you help, support and advice.
Our online will help you plan for managing the challenges of learning and student life, so you can fulfil your potential and have a great student experience.
You can get personal, emotional and mental health support from our Student Wellbeing Service, in person and online. This includes 1–2–1 support as well as courses and workshops that help you better manage stress, anxiety or depression.
If you require extra support because of a disability or additional learning need our specialist team can help you.
They'll help you to:
- discuss and agree on reasonable adjustments
- liaise with other University services and facilities, such as the library
- access specialist study skills and strategies tutors, and assistive technology tutors, on a 1-to-1 basis or in groups
- liaise with external services
Library staff are available in person or by email, phone or online chat to help you make the most of the University’s library resources. You can also request one-to-one appointments and get support from a librarian who specialises in your subject area.
The library is open 24 hours a day, every day, in term time.
The Maths Cafe offers advice and assistance with mathematical skills in a friendly, informal environment. You can come to our daily drop-in sessions, develop your mathematics skills at a workshop or use our online resources.
If English isn't your first language, you can do one of our English language courses to improve your written and spoken English language skills before starting your degree. Once you're here, you can take part in our free In-Sessional English (ISE) programme to improve your English further.
Apply
Unlike undergraduate applications, which go through UCAS, applications for this Master's course are made directly to us.
There's no deadline for applications to this course. We accept applications right up until the start date in September, as long as there are places available. If you wait until September to apply, you may find that the course is full.
If you're applying as an international student, remember that you'll need to leave plenty of time to get your visa organised.
You can find more advice about applying in our Master's application checklist. International students and current students and recent graduates of the СÀ¶ÊÓƵ also have some different application options, which are detailed below.
Extra information for international students
If you're an international student, you can apply directly to us using the same application form as UK students.
You could also get an agent to help with your application. Check your country page for details of agents in your region. To find out what to include in your application, head to the how to apply page of our international students section.
If you don’t meet the English language requirements for this course yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.
Ready to apply?
Start this course in January 2025
Start this course in September 2025
Start this course in January 2026
I'm a current СÀ¶ÊÓƵ student, or a recent СÀ¶ÊÓƵ graduate
If you're currently in your final year of study at СÀ¶ÊÓƵ, or you graduated since July 2024, you're eligible to make a fast track application. You'll have:
- a shorter application form to complete
- access to the 20% Alumni fee discount
- a guaranteed conditional offer, for most Master's courses
After you apply
Once we receive your application, we may ask you for further information. We will then either make you an offer or suggest alternatives if your application is unsuccessful.
You'll usually get a decision within 10 working days, so you shouldn't have to wait too long. Some courses have an interview stage – we'll let you know if you need to prepare for one.
Learn more about how we assess your application.
Admissions terms and conditions
When you accept an offer to study at the СÀ¶ÊÓƵ, you also agree to abide by our Student Contract (which includes the University's relevant policies, rules and regulations). You should read and consider these before you apply.