Data Science BSc

Course overview

We’re living in the age of big data. From the rise of smart devices to the day-to-day services we use, the field of data science has become crucial to making sense of all this data — and keeping major organisations ahead of this fast-moving industry.

At Leeds, we see data science as an exciting and multidisciplinary field broadly at the intersection of mathematics, computer science and communication.

Our Data Science BSc will equip you with advanced mathematical techniques such as machine learning and mathematical modelling to find patterns and to separate features in big data. You’ll also become an effective communicator and strategic thinker, able to understand and resolve complex problems – both individually and collaboratively in multi-professional and interdisciplinary teams. This means, when you graduate, you’ll be a practised programmer, mathematical modeller and strategic communicator, in other words, a well-rounded data scientist.

The extensive skill set you’ll build throughout your degree is highly sought after across almost every industry worldwide, making data science an exceptionally lucrative career choice. If you enjoy doing creative detective work using the scientific tools and techniques to disentangle and tackle real-world problems, then data science at Leeds is the right course for you!

Why study at Leeds:

• Our globally-renowned research in data science, applied mathematics, statistics and financial mathematics feeds directly into the course, shaping your learning with the latest thinking and giving you an insight into relevant topics in industry.
• Learn how to tackle real-world-inspired data problems in a supportive and collaborative environment taught by expert academics who specialise in a variety of areas in the field.
• Tailor the course to suit your interests through interdisciplinary discovery modules that enable you to use your data insights throughout the course to address global challenges such as sustainability.
• Access excellent facilities and computing equipment in collaborative hackathon-style workshops, complemented by social areas, communal problem-solving spaces and quiet study rooms.
• Broaden your experience and enhance your career prospects with our industrial placement opportunities or study abroad programmes.
• Make the most of your time at Leeds by joining our student society MathSoc where you can meet more of your peers, enjoy social events and join the MathSoc football or netball team.

Course details

We are currently reviewing our curriculum as part of a university-wide process. As a result, we are unable to publish module information for this course at this time. The information below provides an overview of what you’ll study and our approach to teaching and assessment. We will update this page as soon as the changes are confirmed. Read more in our terms and conditions.

This content was last updated on 3 April 2023.

This course is, by design, multidisciplinary and follows a centred approach. In first year, the foundations are laid for mathematics, programming and communication, which are then further developed in second and third year.

The course delivery brings together scientific method, teamwork, communication, collaboration and creative problem solving. These skills will be blended in data science applications such as modelling, simulations, creating mock data sets and optimisation questions. You’ll use basic illustrative examples and motivational real-world case studies to understand how this foundational knowledge underpins advanced data science tools and techniques – and how they could be applied to help solve grand challenges too.

You’ll also have the chance to tailor your course with a selection of optional modules – from applied mathematics and statistics to a range of exciting discovery modules – and get involved in your own 40-credit research project in third year.

Each academic year, you'll take a total of 120 credits.

Year 1

In your first year of study, you’ll have the opportunity to learn a range of foundational topics that’ll serve as the basis for the rest of your studies.

In mathematics, you’ll cover topics such as linear algebra, calculus, statistics and probability. On the computational side, you’ll learn the basics of functional programming and software engineering, including data structures, parallelisation and effective algorithms for dealing with big data.

You'll also be exposed to basic principles of information theory, data visualisation, geographical information systems (GIS), natural language processing (NLP) and the social sciences foundations of interpersonal communication along with hands-on practical advice and practice.

These foundational concepts will provide the essential building blocks for data science, equipping you with the skills and knowledge necessary to understand more advanced topics as the course progresses.

Year 2

Your second year will build on the first-year foundations, giving you more insight into applying data science in the ‘real world’. In mathematics, you’ll cover the basics of machine learning, such as clustering, principal component analysis, numerical methods, optimisation and neural networks. You'll also study networks and complex systems, analysing and visualising examples of real-world networks, as well as stochastic processes and statistical inference.

In computer science, you’ll learn more advanced topics such as object-oriented programming, distributed computing, software engineering, data mining and natural language processing. Furthermore, you’ll gain experience in the use of various tools and techniques for collecting, analysing and visualising data.

These topics will provide you with the essential building blocks for data science, equipping you with the understanding you’ll need to apply this discipline in industry.

Year 3

Your third year will blend mathematics, computing and communication, using advanced concepts, tools and techniques to provide a deeper understanding of real-life data science.

You'll learn how to extract data from data bases for data mining, big data visualisation and artificial intelligence. A big component of the year will be a data science dissertation project alongside core data science modules and a range of optional modules in applied mathematics, statistics and discovery.

The dissertation project is your chance to apply everything you’ve learned to a real-world data science problem. Not only will you draw upon the technical knowledge learned throughout your degree, you’ll also use the advanced skills in areas like problem solving, strategic planning, analysis and visualisation to effectively tackle the challenges that arise in your project topic.

The exposure to an industry-relevant challenge is also a great first step in getting a taste for working in data science, building up industry experience before you graduate and demonstrating to employers your extensive skills in this field too.

One-year optional work placement or study abroad

During your course, you’ll be given the opportunity to advance your skill set and experience further. You can apply to either undertake a one-year work placement or study abroad for a year, choosing from a selection of universities we’re in partnership with worldwide.

Learning outcomes

By the end of this degree, you’ll:

• Be able to explain and apply data science core concepts, tools and techniques from mathematical modelling, machine learning, programming, software engineering and communication.
• Be analytical and able to critically evaluate different data science-related approaches, arguments and analyses, and to perform rigorous, robust and reproducible mathematical and computational analyses yourself.
• Be able to conduct independent research or projects - self-managing and appropriately drawing on different sources for information and support - synthesising and integrating the findings critically.
• Be able to appropriately apply fundamental principles of communication in context and to communicate advanced data science concepts, conclusions and recommendations to specialist and non-specialist audiences.
• Be able to express your ideas computationally and to apply principles of programming and software engineering to create, implement or use software appropriately in the analysis and visualisation of big data.
• Apply, blend and contribute your interdisciplinary skills and insights in multiprofessional and multidisciplinary teams, working collaboratively, creatively and professionally in diverse teams, on complex problems from industry to global challenges (e.g. sustainability).
• Be able to articulate how mathematics and data science relate to society and common practices, elucidate the ethical dimension thereof, and act with professional integrity in accordance with ethical professional codes of practice as well as your own values.
• Be a strategic and reflective thinker, being able to identify, articulate and evidence past development and achievements, and plan future strategic goals, such as personal development with reference to external frameworks.

Learning and teaching

Data science is all about being able to apply skills from communication, mathematics and computer science in a real-world context. This course follows input and guidance from employers, data science practitioners, researchers, teachers, students and graduates, combined with cutting-edge pedagogical research such as in the Leeds SCALA approach.

• Student-centred: Supportive, inclusive, flexible, accessible and community-building curricula. 
• Active learning: Cognitively involved students, who are engaged with diverse content and media, and have opportunities to collaborate & participate. 

Your learning will be blended, with a mix of campus-based and online activities alongside study resources. There will be lectures, seminars and problem-solving classes – specifically on the mathematical side – in order to give you the necessary technical proficiency in the foundations for rigorous data science analyses.

There will also be interactive workshops (‘hackathon’-style) to collaborate with your cohort and teaching staff in a very active, hands-on way (problem-based learning). Workshops aim to integrate concepts and tools from lectures in an authentic and motivating context, encouraging you to apply those learned skills in an interdisciplinary context to applications – just like in the real-world.

This also creates an inclusive environment where diversity is strength, and where we can all contribute and learn together as a tight-knit community.

On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

Assessments will give you the opportunity to engage and learn in a variety of ways, which is more representative of what real work is like. In fact, many assessments may also be a chance to build up your own portfolio to help with revision or to showcase your proficiency in the relevant data science tools and techniques to potential employers when you apply for jobs after you graduate.

Whilst exams remain a useful tool for assessing key technical ability – especially for mathematical modules – the course will focus on the ability to apply techniques and tools from mathematics, computing and communication in the context of data science applications. As such, you could also be assessed through a variety of diverse ways throughout the course including project work, report writing, presentations, case studies, group collaborations, videos, blog posts and a portfolio.

Entry requirements

A-level: AAA/A*AB including a minimum of grade A in Mathematics

AAA/A*AB including a minimum of grade A in Mathematics, AAB/A*BB including a minimum of grade A in Mathematics plus Further Mathematics, or AAB/A*BB including a minimum of grade A in Mathematics, plus A in AS Further Mathematics.

Where an A-Level Science subject is taken, we require a pass in the practical science element, alongside the achievement of the A-Level at the stated grade.

Excludes A-Level General Studies or Critical Thinking.

GCSE: English Language at grade C (4) or above, or an appropriate English language qualification. We will accept Level 2 Functional Skills English in lieu of GCSE English.

Other course specific tests:

Extended Project Qualification (EPQ), International Project Qualification (IPQ) and Welsh Baccalaureate Advanced Skills Challenge Certificate (ASCC): We recognise the value of these qualifications and the effort and enthusiasm that applicants put into them, and where an applicant offers the EPQ, IPQ or ASCC we may make an offer of AAB/A*BB including a minimum of grade A in Mathematics, plus A in EPQ/IPQ/Welsh Bacc ASCC.

Alternative qualification

Read more about UK and Republic of Ireland accepted qualifications or contact the School’s Undergraduate Admissions Team.

Alternative entry

We’re committed to identifying the best possible applicants, regardless of personal circumstances or background.

Access to Leeds is an alternative admissions scheme which accepts applications from individuals who might be from low income households, in the first generation of their immediate family to apply to higher education, or have had their studies disrupted.

Find out more about Access to Leeds and alternative admissions.

Typical Access to Leeds offer: ABB including A in Mathematics and pass Access to Leeds OR A in Mathematics, B in Further Mathematics and C in a 3rd subject and pass Access to Leeds

If you do not have the formal qualifications for immediate entry to one of our degrees, you may be able to progress through a foundation year. We offer a Studies in Science with a Foundation Year BSc for students without a science background at A-level and an Interdisciplinary Science with Foundation Year BSc for applicants who meet specific widening participation criteria.

International Foundation Year

International students who do not meet the academic requirements for undergraduate study may be able to study the University of Leeds International Foundation Year. This gives you the opportunity to study on campus, be taught by University of Leeds academics and progress onto a wide range of Leeds undergraduate courses. Find out more about International Foundation Year programmes.

English language requirements

IELTS 6.0 overall, with no less than 5.5 in any one component, or IELTS 6.5 overall, with no less than 6.0 in any one component, depending on other qualifications present. For other English qualifications, read English language equivalent qualifications.

Improve your English
If you're an international student and you don't meet the English language requirements for this programme, you may be able to study our undergraduate pre-sessional English course, to help improve your English language level.

Fees

UK: £9,250 (per year)

International: £27,250 (per year)

Tuition fees for UK undergraduate students starting in 2023/24 and 2024/25
Tuition fees for UK full-time undergraduate students are set by the UK Government and will remain capped at £9,250 for 2023/24 and 2024/25. The fee may increase in future years of your course in line with inflation only as a consequence of future changes in Government legislation and as permitted by law.

Tuition fees for international undergraduate students starting in 2023/24 and 2024/25
Tuition fees for international students for 2023/24 and 2024/25 are available on individual course pages.

Tuition fees for a study abroad or work placement year
If you take a study abroad or work placement year, you’ll pay a reduced tuition fee during this period. For more information, see Study abroad and work placement tuition fees and loans.

Read more about paying fees and charges.

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There is help for students in the form of loans and non-repayable grants from the University and from the government. Find out more in our Undergraduate funding overview.

Applying

Apply to this course through UCAS. Check the deadline for applications on the UCAS website.

We may consider applications submitted after the deadline. Availability of courses in UCAS Extra will be detailed on UCAS at the appropriate stage in the cycle.

Read our guidance about applying and writing your personal statement.

International students apply through UCAS in the same way as UK students. Our network of international representatives can help you with your application. If you’re unsure about the application process, contact the admissions team for help.

Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

University of Leeds Taught Admissions Policy 2024

Contact us

School of Mathematics Undergraduate Admissions

Email: maths.admiss@leeds.ac.uk
Telephone:

Career opportunities

Data science has become indispensable to so many industries worldwide – meaning you’ll be in high demand with a wealth of job prospects open to you when you graduate.

Leeds, in particular, is a major hub for data scientists – with a strong presence of high-profile data science start-ups and large tech companies, as well as many key players in the fintech sector, such as banks, consultancies and accountancy firms too.

As a University of Leeds student, you’ll benefit from our strong industry links, too, which’ll give you the platform to network with potential employers and gain valuable work experience before you graduate.

Plus, University of Leeds students are among the top 10 most targeted by top employers according to The Graduate Market 2023, High Fliers Research.

With the combination of specialist and transferable skills you’ll learn on this BSc, you could go into areas like data analysis, machine learning engineering or data science in strategy or in communication across a range of fields and industries like:

• technology
• finance
• healthcare
• charities
• government

Careers support

At Leeds, we help you to prepare for your future from day one. Our Leeds for Life initiative is designed to help you develop and demonstrate the skills and experience you need for when you graduate. We will help you to access opportunities across the University and record your key achievements so you are able to articulate them clearly and confidently.

You will be supported throughout your studies by our dedicated Employability team, who will provide you with specialist support and advice to help you find relevant work experience, internships and industrial placements, as well as graduate positions. You’ll benefit from timetabled employability sessions, support during internships and placements, and presentations and workshops delivered by employers.

You will also have full access to the University’s Careers Centre, which is one of the largest in the country.

Study abroad and work placements

Studying abroad is a unique opportunity to explore the world, whilst gaining invaluable skills and experience that could enhance your future employability and career prospects too.

From Europe to Asia, the USA to Australasia, we have many University partners worldwide you can apply to, spanning across some of the most popular destinations for students.

This programme offers you the option to spend time abroad as an extra academic year and will extend your studies by 12 months.

Once you’ve successfully completed your year abroad, you’ll be awarded the ‘international’ variant in your degree title which demonstrates your added experience to future employers.

Find out more at the Study Abroad website.

Work placements

A placement year is a great way to help you decide on a career path when you graduate. You’ll develop your skills and gain a real insight into working life in a particular company or sector. It will also help you to stand out in a competitive graduate jobs market and improve your chances of securing the career you want.

Benefits of a work placement year:

• 100+ organisations to choose from, both in the UK and overseas
• Build industry contacts within your chosen field
• Our close industry links mean you’ll be in direct contact with potential employers
• Advance your experience and skills by putting the course teachings into practice
• Gain invaluable insight into working as a professional in this industry
• Improve your employability

If you decide to undertake a placement year, this will extend your period of study by 12 months and, on successful completion, you will be awarded the ‘industrial’ variant in your degree title to demonstrate your added experience to future employers.

With the help and support of our dedicated Employability team, you can find the right placement to suit you and your future career goals.

Find out more about Industrial placements.

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