• Undergraduate

Data Science with Foundation Year BSc (Hons)

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Overview

Overview

Why study at the University of West London? 
  • Our computer science courses are ranked #1 in London for overall student satisfaction in this year's NSS
  • Ranked 30th university in the UK - The Guardian University Guide 2025
  • Number 1 London university for overall student satisfaction - National Student Survey 2024**
  • Best university for Student Experience and Teaching Quality in the UK - The Times and Sunday Times Good University Guide 2024

As a graduate of a BSc Data Science degree, you will offer your employers outstanding skills in modelling, statistical analysis, and software development.

The course offers a balance between theory and applications, allowing you to both develop a deep understanding of mathematical and statistical tools whilst, being able to translate these into concrete computer-based solutions.

Upon successful completion of this degree, you will be well-equipped to enter a career in data analysis, modelling, finance/insurance, or in the computing industry. You may also choose to further specialise by undertaking postgraduate studies in subjects such as computer science, cyber security, data science, or artificial intelligence.

Foundation Year 

The foundation year course is designed to equip you with the skills and knowledge you need to continue onto your Honours degree. You will study a range of subjects that will underpin your future study and also gain valuable experience of university life, with full access to campus facilities. Successful completion of the year allows you to progress straight onto Level 4 of this course. Please note that a £2000 Path to Success bursary is available to all UK foundation year students, which is non-repayable.

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Select your desired study option, then pick a start date to see relevant course information:

Study options:
We support flexible study by offering some of our courses part-time or via distance learning. To give you real world experience before you graduate, we also offer some courses with a placement or internship. All available options are listed here. Your choices may affect some details of your course, such as the duration and cost per year. Please re-check the details on this page if you change your selection.
Without Foundation Year
Duration: 3 years

Start date:

If your desired start date is not available, try selecting a different study option.

Why study Data Science with Foundation Year with us?

Why study Data Science with Foundation Year with us?

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What our students say…

I picked UWL because the facilities looked amazing and I loved the focus on helping students secure the right career once they graduate.

Damian Pop
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Course detail & modules

Course detail & modules

The course introduces you to mathematical, statistical, and computing techniques that form the basis of many tools used in industry, engineering, business, and education, using information and data as an integral part of problem solving and decision making.

This data science course aims to produce graduates who:

  • meet employer requirements for well-trained, competent, and adaptable professionals with expert knowledge in data-driven decision making
  • are highly numerate and able to use this to applications for modelling purposes
    are independent learners, able to acquire new skills and continue to build their knowledge, to adapt to a rapidly changing job market
  • can undertake postgraduate studies in several disciplines related to data science, computing and artificial intelligence
  • are strong communicators and have strong interpersonal and team working skills
    have knowledge of ethical issues, particularly the need for sensitivity in data handling and decision making.

Throughout your studies you can expect a supportive learning environment that will:

  • develop your interpersonal skills
  • raise your self-awareness
  • encourage personal and career growth
  • stimulate the idea of lifelong learning.

You can expect regular contact with employers and career advisers, as an integral part of taught modules and extracurricular activities. We offer an inclusive and diverse learning environment that makes use of a variety of teaching and learning methods, and encourages teamwork. 

Foundation year

There are many reasons for joining a foundation year course; you may not have the exact subjects or grades at A level to meet the entry requirements, you may have been living abroad or want to change direction with your career. Whatever your starting point, the foundation year offers a firm grounding in the skills and knowledge that you will need to get the most from your studies and thrive at University. Successful completion of the foundation year allows you to progress straight onto Level 4 of this course.
 

Compulsory modules

  • Personalised Learning

    The Personalised Learning module is intended to equip you with the study skills needed to successfully progress onto level 4, the first year of undergraduate study. Tutor group sessions are an integral part of the module, where you will consolidate your learning and frame it in the context of your subject area. The module will focus on various aspects of study skills, such as those skills related to reading and writing, learning approaches, problem-solving techniques, critical thinking, researching, referencing, plagiarism, legal research and time management.

  • Introduction to Statistics

    This module aims to provide a basic knowledge of how to summarise, analyse and interpret data, provide an overview of sampling and experimentation in the mathematical sciences and engineering field, and deliver an introduction to modelling a linear relationship between variables.

  • Introduction to Computer Technologies

    Some of the technologies you will cover include:

    Hardware (computer systems)
    • CPU
    • memory
    • motherboard
    • hard drive disk
    • secondary storage
    • graphic cards
    • sound cards
    • input and output devices
    • peripherals (printers, mobile computing devices, tablets, smartphones, etc) 
    Software
    • system software: operating systems, utility programs
    • application software: general purpose application software, special purpose application software, bespoke application software
    Communication Technologies
    • computer networks and components
    • protocols and communication methods
    Social and Economic Impact
    • automation
    • cloud computing
    • Internet of Things

  • Study Skills for Success

    This module will enable you to read critically, present an argument, and distinguish between the quality and suitability of materials. It will prepare you to use and evaluate a range of evidence sources throughout your degree.

  • Introduction to Computing Mathematics

    You will learn the core mathematical skills and statistical concepts and techniques to be able to effectively analyse and present information.

    You will develop skills in expressing problems in mathematical language, finding solutions to problems and communicating mathematical ideas clearly and succinctly. 

    You will gain essential mathematical skills that will prepare you for other modules.  

  • Introduction to Web Design and Development

    You will cover the basics of web design and development, learning how to integrate text, graphics and behaviour to create interactive webpages using HTML5, CSS3 and Javascript.

    Other aspects will be covered such as historic development of the web, architecture and basic client server architecture, protocols such as HTTP, issues of accessibility and usability, standards and standardisation organisations (W3C, Internet Working Group) and security (HTTPS, firewalls, certificates). 

Compulsory modules

  • Probability and Statistics

    This module is an introduction to probability theory and statistical methods. The module leads to a deeper understanding of probability distributions, random variables and their role in sampling. Tools such as hypothesis testing are presented and a basic introduction to the statistical software SPSS is provided.

  • Linear Algebra

    The aim of this module is to extend your knowledge of matrices, vectors and systems of linear equations and to introduce the abstract concepts of vector spaces, linear maps and inner products.

  • Programming

    This module covers basic programming concepts and fundamentals using Java programming language. Content includes:

    • an overview of programming paradigms and techniques
    • analysis of problems and design using pseudo-code and flowcharts
    • basic program elements and structure
    • development supported by version-controlled code repositories.

  • Calculus 1

    This module introduces you to the most important techniques in Calculus. In particular, the module leads to a deeper understanding of the concepts of differentiation and integration. Tools and techniques for differentiation and integration will be presented in detail.

  • Data Communications

    This module adopts a top-down approach to data communication networking, beginning at the application layer and working down towards the physical layer. After completing the five-layer network architecture, the module focuses on wireless network and its security. In summary, the following aspects will be covered:

    • application layer
    • transport layer
    • network layer
    • data link layer
    • 802.11 WIFI protocol
    • principle of cryptography
    • Wireless security: WEP and WPA

  • Algorithms and Data Types

    This module will help you to gain the knowledge and competence to deal with basic data structures and algorithms. You will learn how to specify collections using abstract data types (ADTs) and to implement them using a variety of techniques such as linked lists and trees. You'll also use a range of algorithms, including searching and sorting.

Compulsory modules

  • Multi-variate Calculus

  • Artificial Intelligence

    In this module you will gain insights into key techniques within the field of artificial intelligence (AI). Aspects of AI you'll cover include agents, environments and learning as well as techniques such as regression, classification, clustering, reinforcement learning, learning recommendation and decision support systems.

  • Theory of Computation

    You will gain the knowledge and understanding of fundamental concepts of computational theory and computational complexity. You will learn how to examine whether a given problem can be solved computationally.

  • Numerical Methods

    This module aims to introduce you to the numerical techniques required to solve different mathematical problems motivated by the engineering and the science sector.

  • Statistical Modelling

    This module aims to develop understanding and proficiency in statistical modelling by introducing you to the normal theory linear model. It will provide you with the ability to formulate and apply these models in a range of practical settings, to carry out associated inference appreciating how this relates to the general likelihood inferential framework, and to perform appropriate model selection and model checking procedures.

  • Applications of AI

Compulsory modules

n addition to the three compulsory modules, you will study two modules (20 credits each) from the following options:

Ordinary and Partial Differential Equations OR Robotics and AI
Operational Research and Optimisation OR Natural Language Processing

  • Machine Learning

    Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.

    This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.

  • Databases and Analytics

    There has been an explosion in data, much of which is not fully structured, but contains valuable information such as search trends, consumer behaviour and other patterns. This module aims to cover some of the developments in the broad range of "Big Data" problems. It will give you a good understanding of data structures, software development procedures and the range of analytical tool used to undertake a wide range of standard and custom analyses to provide data solutions to these issues. 

  • Project

    You will investigate a topic of interest and prepare a project proposal. You will then present your ideas to the school for approval and once this has been approved, you will begin a detailed literature review of your chosen field. You will choose and follow a suitable development methodology leading to an implementation which you will evaluate.

Optional modules

  • Machine Learning

    Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.

    This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.

  • Cyber Security

    You will be introduced to fundamental cyber security concepts including Cryptography, Authentication, Authorisation, and Auditing with an emphasis on their application.

  • Distributed Systems

    You will cover the fundamental concepts and models, algorithmic and architectural techniques, developmental principles and approaches of modern distributed systems. You will enhance your critical analysis, problem solving and technical skills in distributed systems software design and implementation.

  • Databases and Analytics

    There has been an explosion in data, much of which is not fully structured, but contains valuable information such as search trends, consumer behaviour and other patterns. This module aims to cover some of the developments in the broad range of "Big Data" problems. It will give you a good understanding of data structures, software development procedures and the range of analytical tool used to undertake a wide range of standard and custom analyses to provide data solutions to these issues. 

  • Human-Centred Computing

    This module is about human and technical aspects of interactive computing systems and organisations. In the course of taking this module, you'll consider the interplay between human users, designers, developers and computers. Therefore, its basis is in psychology and human factors as well as in software engineering and interaction design.

  • Functional Programming

    This module provides you with the chance to gain further experience with another programming paradigm. You will learn how to write programs using a functional programming language, Haskell. 

    Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. For example, building an application with Functional Programming following the model Function as a Service (FAAS) is one way of achieving a "serverless" architecture and is used when building microservices applications of cloud computing.

Entry requirements

Entry requirements

72 UCAS points required from level 3 qualifications

These can include:

  • A-Levels at grades B and C (if you have two A-Levels) or grades D, D and D (if you have three), or above
  • BTEC Extended Diploma with Merit, Merit, Pass
  • Access to HE Diploma
  • T-Levels

You also need GCSE English and Maths (grade 9 – 4 / A* - C) or Level 2 equivalents.

Looking for BSc (Hons) Data Science without Foundation Year?

View course
Whether you are changing career or don't have the exact subjects and grades required for this course, you might want to choose this course with a foundation year. This will give you an extra year's study to prepare you for the standard degree programme, where you can go on to graduate with a full Honours degree. Follow the link to see full details of the course with foundation year.

You may be eligible for a student loan to cover the cost of tuition fees, or a maintenance loan. Additional funding is available to some types of students, such as those with dependants and disabled students.

Looking for BSc (Hons) Data Science without Foundation Year?

View course
Whether you are changing career or don't have the exact subjects and grades required for this course, you might want to choose this course with a foundation year. This will give you an extra year's study to prepare you for the standard degree programme, where you can go on to graduate with a full Honours degree. Follow the link to see full details of the course with foundation year.
5.5 IELTS or above

You need to meet our English language requirement - a minimum of IELTS 5.5 for each of the four individual components (Reading, Writing, Speaking and Listening). Visit our English language requirements page for information on other English language tests we accept.

You also need academic qualifications at the same level as UK applicants. In some countries where teaching is in English, we may accept local qualifications. Check for local equivalents. 

We offer pre-sessional English language courses if you do not meet these requirements.

Find out more about our English Language courses.

Looking for BSc (Hons) Data Science without Foundation Year?

View course
Whether you are changing career or don't have the exact subjects and grades required for this course, you might want to choose this course with a foundation year. This will give you an extra year's study to prepare you for the standard degree programme, where you can go on to graduate with a full Honours degree. Follow the link to see full details of the course with foundation year.

You may be eligible for a student loan to cover the cost of tuition fees, or a maintenance loan. Additional funding is available to some types of students, such as those with dependants and disabled students.

Looking for BSc (Hons) Data Science without Foundation Year?

View course
Whether you are changing career or don't have the exact subjects and grades required for this course, you might want to choose this course with a foundation year. This will give you an extra year's study to prepare you for the standard degree programme, where you can go on to graduate with a full Honours degree. Follow the link to see full details of the course with foundation year.
Fees & funding

Fees & funding

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Please note:

  • Fees for the 2026/27 academic year and onwards may be subject to Government regulation and change.
  • Tuition fees are charged for each year of your course. If your course runs for two years or more, you will need to pay the fee for each academic year at the start of that year.
  • If your course runs for less than two years, the cost above is for your full course and you will need to pay the full fee upfront.
  • If no fee is shown above then the fees for this course are not available yet. Please check again later for updates.

Funding your studies

You may be eligible for a student loan to cover the cost of tuition fees, or a maintenance loan. Additional funding is available to some types of students, such as those with dependants and disabled students.

Foundation year bursary

If you are a UK student joining a foundation year course with UWL, you will receive a £2000 Path to Success bursary to support your studies. This is not a loan and does not need to be repaid. You will receive £500 per year subject to your attendance, engagement and progression through your studies. 

To find out more, explore our Undergraduate scholarships and bursaries page.

Funding your studies
{{ formatCurrencyValue(currentVariantData.field_p_cv_int_main_fee.name) }} per year*

Please note:

  • Fees for the 2026/27 academic year and onwards may be subject to Government regulation and change.
  • Tuition fees are charged for each year of your course. If your course runs for two years or more, you will need to pay the fee for each academic year at the start of that year.
  • If your course runs for less than two years, the cost above is for your full course and you will need to pay the full fee upfront.
  • If no fee is shown above then the fees for this course are not available yet. Please check again later for updates.

International students - funding your studies

We offer scholarships for international students including International Ambassador Scholarships. 

Further information about funding and financial support for international students is available from the UK Council for International Student Affairs.

 

Financial support for international students
Teaching staff

Teaching staff

Thomas Madsen is smiling in front of a white background

Dr Thomas Madsen

Before joining the University of West London, Dr Madsen was a Lecturer at University of Buckingham. Before that he held academic positions at a number of international institutions, including at Aarhus University (Denmark), Centro di Ricerca Matematica Ennio De Giorgi (Pisa) and King’s College London.

Most of Dr Madsen’s research and publications are in the area of differential geometry. He particularly enjoys analysing and finding explicit solutions to partial differential equations that arise in a geometric context (e.g. Einstein’s equations), using symmetry techniques.

Before joining the University of West London, Dr Madsen was a Lecturer at University of Buckingham. Before that he held academic positions at a number of international institutions, including at Aarhus University (Denmark), Centro di Ricerca Matematica Ennio De Giorgi (Pisa) and King’s College London.

Most of Dr Madsen’s research and publications are in the area of differential geometry. He particularly enjoys analysing and finding explicit solutions to partial differential equations that arise in a geometric context (e.g. Einstein’s equations), using symmetry techniques.

Study & career progression

Study & career progression

Two students walking through campus, smiling and socialising.

Upon successful completion of the foundation year, you can progress onto a computer science-related undergraduate degree.

How to apply

How to apply

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Important notes for applicants

Disclaimer

*Modern universities - defined as higher education institutions that were granted university status in, and subsequent to, 1992.

**The National Student Survey 2023 and 2024 - Average of answers to all questions by registered student population. Excludes specialist institutions.

Testimonials - our students or former students provided all of our testimonials - often a student from the course but sometimes another student. For example, the testimonial often comes from another UWL student when the course is new.

Optional modules - where optional modules are offered they will run subject to staff availability and viable student numbers opting to take the module.

Videos - all videos on our course pages were accurate at the time of filming. In some cases a new Course Leader has joined the University since the video was filmed.

Availability of placements - if you choose a course with placement/internship route we would like to advise you that if a placement/internship opportunity does not arise when you are expected to undertake the placement then the University will automatically transfer you to the non-internship route, this is to ensure you are still successful in being awarded a degree.