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What makes BSc (Hons) Data Science at the University of Worcester special?

The top 5 companies in the world today all have one thing in common, they are all data driven organisations. On this degree you will learn the skills you need have a career in this exciting field, from the basics of Computing, Programming and Coding for Web and Mobile, along with Data Mining, Information Systems, Mathematical and Statistical methods and other techniques that are needed in a data driven environment. In the later years of your degree, you will discover Machine Learning, Cyber Security and Natural Language Processing. 

Studying this course over 4 years offers the opportunity to take a one-year work placement in industry, should you wish to, in order to gain vital real-world experience.



Key features

  • Study the core of university-level Computing, Data, Data Analysis and Data Science degrees
  • Additional modules featuring mini-projects in mathematical modelling and data analysis, together with transferrable skills in using computer software packages, conducting research and communication
  • Some modules have opportunities to gain professional qualifications alongside your final degree
  • Work placement opportunities with numerous companies such as Bosch, IBM and Clearview
  • Opportunity to apply skills and knowledge from across the whole course in an applied final-year project
Entry requirements

Entry requirements

UCAS tariff points

Entry Requirements

96 UCAS Tariff points (for example, CCC at A Level).

Applicants with no formal qualifications may be considered for Mature Student Entry Routes.

T Levels may be used to meet the entry tariff requirements for this course. Find out more about T levels as UCAS tariff points here.

Other Information

If you have any questions about entry requirements, please contact the Admissions Office on 01905 855111 or email for advice.

Further information about the UCAS Tariff can be obtained from the UCAS website.

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Course content

Course content

Our courses are informed by research and current developments in the discipline and by feed back from students, external examiners and employers. Modules do therefore change periodically in the interests of keeping the course relevant and reflecting best practice. The most up-to-date information will be available to you once you have accepted a place and registered for the course. If there are insufficient numbers of students interested in an optional module, this might not be offered, but we will advise you as soon as possible and help you choose an alternative.

The following modules will be studied by all students throughout the degree programme:

Year 1

  • Foundations of Computing
  • Web Technologies
  • Introduction to OO Programming
  • Mathematical Fundamentals
  • IT Systems Fundamental

Year 2

  • Systems Analysis & Design
  • Distributed Systems
  • Data Mining
  • Statistics
  • Mobile Application Development

Year 3

  • Data Science Project
  • Machine Learning
  • Practical Database Applications
  • Cyber Security
  • Advanced Machine Learning
  • Internet of Things
  • Natural Language Processing
Teaching and assessment

Teaching and assessment

The University places emphasis on enabling you to develop the independent learning capabilities that will equip you for lifelong learning and future employment, as well as academic achievement. A mixture of independent study, teaching, academic support through integrated coaching and the personal academic tutoring system enables you to reflect on progress and build up a profile of skills, achievements and experiences that will enable you to flourish and be successful.


You are taught through a combination of interactive workshops, lab sessions, lectures and seminars. Interactive workshops and lab sessions take a variety of formats and are intended to enable the application of learning through practical activities in our dedicated computing labs; be that on your own or in small groups. Seminars enable the discussion and development of understanding of topics covered in lectures as well as opportunities to practice skills learnt.

In addition, meetings with personal academic tutors are scheduled on at least four occasions during your first year.

The University places emphasis on enabling students to develop the independent learning capabilities that will equip you for lifelong learning and future employment, as well as academic achievement. A mixture of independent study, teaching and academic support from Student Services and Library Services, and also the personal academic tutoring system enables you to reflect on progress and build up a profile of skills, achievements and experiences that will help you to flourish and be successful.

Contact time

In a typical week students will have 12 contact hours of timetabled teaching in lectures, seminars and small-group work. This is in the form of on campus face-face teaching in groups of around 30 students. In the final year there is normally slightly less contact time in order to do more independent study. 

Typically, class contact time will be structured around:

  • Information giving, facilitated discussions, small group work, presentations
  • Practical skills – the opportunity to practise group facilitation, presentation, communication and listening skills
  • Visiting speakers and opportunities to visit other settings are regular features of the course.
  • Most teaching will take place in state-of-the-art PC labs using a variety of software specific to each module

Independent self-study

In addition to the contact time, full-time students are expected to undertake around 24 hours of personal self-study per week, plus additional preparation for assessments and examinations. Typically, this will involve meeting with individual tutors to discuss progress and feedback, completing activities, creating and testing artefacts, reading journal articles and books, working on individual and group projects, undertaking research in the library and online.

These activities, challenges and further reading are posed via the University Virtual Learning Environment. Students will also have access to software and other services required for independent studies available for use on University lab machines or for download for home use where possible.

In addition to this, students will spend time sharing ideas with fellow students, taking part in extra-curricular learning activities and engaging with external employers.

Independent learning is supported by a range of excellent learning facilities, including the Hive and library resources, the virtual learning environment, and extensive electronic learning resources as well as our network of employers and entrepreneurs. 


  • 3 years full-time
  • 4 years full-time including one year placement
  • 4-6 years part-time


Timetables are normally available one month before registration. Please note that whilst we try to be as student friendly as possible, scheduled teaching can take place on any day of the week; and some classes can be scheduled in the evenings.


All modules have both formative and summative assessment elements. Formative assessment allows tutors and students to recognise strengths and weaknesses in learning and to address those issues immediately. Summative assessments are graded and count towards the final module grade, and they are assessed against the specific module learning outcomes.

Typically 15 credit/one semester modules will have 1-2 assessment items. 30 credit/two semester modules will have 2-3 assessments.

Across each individual year and cumulatively across all three years the concept of continuous assessment and/or building up expertise in different assessment types applies. This includes expanding upon and enhancing previous artefacts culminating in a final year project.

Different types of employability skills are embedded in all modules including technical presentation, problem decomposition and design, build and test skills. A variety of assessment types (reports, portfolios, presentations, essays and a final year research or consultancy project) are designed to suit different learning styles 

The typical formal summative assessment pattern for each year of the course is:

Year 1 
  • 1 x Essay
  • 1 x Practical Assessment
  • 2 x Report (1500 – 2000 word)
  • 2 x Presentation
  • 2 x Unseen Examination (1hr)
  • 1 x Project
  • 3 x Portfolio of work 
Year 2
  • 1 x Report (2000 word)
  • 1 x Presentation
  • 1 x Unseen Examination (1hr)
  • 2 x Project
  • 4 x Portfolio of work
  • 1 x Case Study 
Year 3
  • 3 x Practical Assessment
  • 4 x Report (1500 - 3000 words)
  • 3 x Presentation
  • 1 x Dissertation
  • 1 x Portfolio of work 

Programme specification

For comprehensive details on the aims and intended learning outcomes of the course, and the means by which these are achieved through learning, teaching and assessment, please download the latest programme specification document.

Meet the team

You will be taught by a teaching team whose expertise and knowledge are closely matched to the content of the modules on the course. The team includes senior academics, professional practitioners with industry experience, and visiting speakers with specialised expertise. Teaching is informed by the research and consultancy work carried out by staff and you can learn more about the staff by visiting our staff profiles.

Here are a few of the current members of the department who teach on this course:


Andrew Robinson

Andrew has worked in the computer graphics industry for over 25 years, for a wide range of blue-chip clients.

He now teaches Creative Computing and Web Design and Applied Drone Technology to undergraduate students, supervises graduate and undergraduate projects, and provides support to students in the Business School Media Lab.  

Pete Clews

Peter Clews

Peter has a wide variety of industry experience, including three years in database administration and data analysis for Mercedes-Benz dealerships. He has a BSc Computing with Business from the University of Worcester, where he was awarded the Academic Achievement Scholarship for his first-year results. He has an MSc in Business Intelligence from Birmingham City University (with distinction), where the topic of his dissertation was a review of rudimentary methods of sarcasm classification in tweets.

Peter currently assists with delivering the undergraduate database modules, as well as contributing to the postgraduate corporate intelligence modules. His research interests include data mining, text mining, machine learning algorithms and database architectures. Peter also has a keen interest in the provision of support for students on the autistic spectrum within higher education.

Headshot of Bradley Carwardine

Bradley Carwardine

Bradley has extensive industry experience in many technology sectors. He has worked in commercial programming, networking infrastructure installation and has supported the UK Special Forces in a variety of technological integration projects. Bradley is a qualified teacher and has been teaching computer science for over 15 years. He has been teaching in the FE and HE for the last 5 years.


Dr Colin B Price

Colin has spent his entire career in education. From the early years teaching Physics at the British School of Brussels to his current post as Principal Lecturer in Computing, Colin has always strived to integrate his research and teaching. He has held faculty positions at the Catholic University of Leuven, Belgium, where he has taught Electronic Engineering and also Physics to Medical Science students. 

PhD Electrotechnical Engineering (Katholieke Universiteit Leuven, Belgium)

MA Natural Sciences (Cantab)

BA Natural Sciences (Cantab) 

Richard Wilkinson

Richard Wilkinson

Richard is a Senior Lecturer in Computing, as well as the Head of the Department of Computing, teaching on a variety of modules for both Computing, Business IT and Business degrees. Here at the University of Worcester Richard leads on our Global Partnerships with QLIK, IBM Watson Analytics & Microsoft Dynamics.

Richard is published in the field of IT in Higher Education, is a Senior Fellow of the HEA, a member of the British Computer Society (BCS) and an External Examiner.


Dr Pete Moody

Within Worcester Business School, Pete’s roles include being the Exams and Assessment Officer, and being the link tutor for courses run by CIPP. From the student perspective, Pete is the final year projects co-ordinator. He is also one of the Business School's Academic Integrity Tutors: while this unfortunately means that he has to deal with occasional cases of suspected cheating, Pete sees it as more to do with helping students to use sources properly in their assignments, and so not do anything that could be seen as cut-and-paste plagiarism. Pete’s teaching is mainly to do with computer hardware and networks.



Demand for workers with specialist data skills like data scientists and data engineers has more than tripled over five years (+231%), according to a labour market analysis commissioned for ‘Dynamics of data science skills’, a new Royal Society report. Demand for all types of workers grew by 36% over the same period.

This degree programme will equip you with the skills required to start a career in a digital world where there is currently a huge talent shortage and demand for jobs is continuing to grow in importance.

To advance your career prospects we have implemented the following strategies into the Data Science BSc (Hons) degree:

  • We have ensured that the course is designed in consultation with employers, aligned with industry standards, and taught by experienced computing professionals
  • The option of a paid placement year and opportunity to learn via live work-based projects, allows to gain experience you to earn as you learn
  • We give you the opportunity to gain additional professional qualifications and certification during your degree (should you wish)
  • Employment preparation workshops which include CV preparation, mock interviews/assessment centres, and meetings with employers are built into the syllabus

Fees and funding

Full-time tuition fees

UK and EU students

The standard fee for full-time home and EU undergraduate students enrolling on BA/BSc/LLB degrees and FdA/FdSc degrees in the 2024/25 academic year is £9,250 per year.

For more details, please visit our course fees page.

International students

The standard tuition fee for full-time international students enrolling on BA/BSc/LLB degrees and FdA/FdSc degrees in the 2024/25 academic year is £16,200 per year.

For more details, please visit our course fees page.

Part-time tuition fees

UK and EU students

The standard tuition fees for part-time UK and EU students enrolling on BA/BSc/LLB degrees and FdA/FdSc degrees in the academic year 2024/25 are £1,156 per 15-credit module, £1,542 per 20-credit module, £2,312 per 30-credit module, £3,083 per 40-credit module, £3,469 per 45-credit module and £4,625 per 60 credit module.

For more details, please visit our course fees page.

Course-related costs not included in the fees

Every course has day-to-day costs for basic books, stationery, printing and photocopying. The amounts vary between courses.

24/7 access to computers is provided at the University and software is made available at either no additional cost or minimal cost. Students may also want to purchase a new PC/laptop or upgrade existing equipment for their own usage.


Finding the right accommodation is paramount to your university experience. Our halls of residence are home to friendly student communities, making them great places to live and study.

We have over 1,000 rooms across our range of student halls. With rooms to suit every budget and need, from our 'Chestnut Halls' at £131 per week to 'Oak Halls' at £221 per week (2024/25 prices).

For full details visit our accommodation page.

How to apply

How to apply

Applying through UCAS

Data Science BSc (Hons) - I111
Data Science (Placement Year) BSc (Hons) - 4 Year - I112

UCAS is the central organisation through which applications are processed for entry onto full-time undergraduate courses in Higher Education in the UK.

Read our How to apply pages for more information on applying and to find out what happens to your application.

UCAS Codes

Data Science BSc (Hons) - I111

Apply via UCAS

Data Science (Placement Year) BSc (Hons) - 4 Year - I112

Apply via UCAS

Get in touch

If you have any questions, please get in touch. We're here to help you every step of the way.


Admissions Office

Akinola Olumide Siyanbola

Admissions tutor