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What makes studying Artificial Intelligence (AI) at Worcester special?

At Worcester you'll gain a deep understanding of both human and machine intelligence. This nature of this course makes AI an intellectually stimulating and diverse area of study. One of the most compelling aspects of AI is its ability to solve complex problems and automate tasks, leading to significant advancements in technology and society. For instance, AI algorithms power self-driving cars, enhance medical diagnostics, and enable personalized learning experiences.

The promise of AI to improve efficiency, accuracy, and decision-making in various industries makes its study highly relevant and impactful. Furthermore, AI research addresses fundamental questions about consciousness, learning, and perception, pushing the boundaries of what machines can achieve. This exploration into the unknown drives innovation and sparks curiosity among researchers and students alike. The rapid pace of AI development and its ethical implications also add a layer of importance to studying the field.

Understanding AI's societal impacts, including issues of bias, privacy, and job displacement, is crucial for developing responsible and fair technologies. Thus, studying AI is not just about technical prowess but also about contributing to a future where technology benefits humanity as a whole.

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

 

Overview

Overview

Key features

  • Study the core of university-level Computing, Artificial Intelligence, 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

96
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 admissions@worc.ac.uk for advice.

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

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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.

Teaching

You will be taught through a combination of interactive workshops, lectures, seminars, laboratory practical sessions, practical activities, etc. Some examples include:

  • Interactive workshops take a variety of formats and are intended to enable the application of learning through discussion and small group activities and can incorporate short lectures, worksheets and tutor-supported activities.
  • Flipped lectures where lecture content and activities are provided prior to an interactive workshop to provide background and context to the sessions.
  • Seminars enable the discussion and development of understanding of topics covered in lectures, and laboratory practical sessions are focused on developing subject-specific skills and applied individual and group project work.

We also make use of real-world case studies, oral presentations, mock examinations, hands on experience working with contemporary data analytic tools and programming environments, guest speaker inputs, and self-directed research. You do not merely learn in isolation and using the university's Virtual Learning Environment allows for online collaborative activities to take place. 

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 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.

³ÉÈËBÕ¾ 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. 

Duration

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

Timetables

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.

Assessment

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 .

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 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 ³ÉÈËBÕ¾, 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

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 ³ÉÈËBÕ¾ 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.

Careers

Careers

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
Costs

Fees and funding

Full-time tuition fees

UK and EU students

The Government has announced that it will increase tuition fees and maintenance loans by 3.1% from the 2025/26 academic cycle. Subject to approval, the University intends to increase our tuition fees in line with this and as per our terms and conditions. This means that from September 2025 the standard fee for full-time home and EU undergraduate students enrolling on BA/BSc/LLB degrees and FdA/FdSc degrees will be £9,535 per year.

For more details on course fees, 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 2025/26 academic year is £16,700 per year.

For more details on course fees, please visit our course fees page.

Part-time tuition fees

UK and EU students

The Government has announced that it will increase tuition fees and maintenance loans by 3.1% from the 2025/26 academic cycle. Subject to approval, the University intends to increase our tuition fees in line with this and as per our terms and conditions. This means that from September 2025 the tuition fees for part-time UK and EU students on BA/BSc/LLB degrees and FdA/FdSc degrees will be £1,190.83 per 15-credit module, £1,587.77 per 20-credit module, £2,381.66 per 30-credit module, £3,175.55 per 40-credit module, £3,572.50 per 45-credit module and £4,763.32 per 60 credit module.

For more details on course pages, 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.

Accommodation

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 'Traditional Halls' at £131 per week to 'Ensuite Premium Halls' at £228 per week (2025/26 prices).

For full details visit our accommodation page.

How to apply

How to apply

Applying through UCAS

Artificial Intelligence BSc (Hons) - I111
Artificial Intelligence (Placement Year) BSc (Hons) - 4 Year - I112

 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

Artificial Intelligence BSc (Hons) - I111

Artificial Intelligence (Placement Year) BSc (Hons) - 4 Year - I112

Get in touch

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

Admissions

Admissions Office

Akinola Olumide Siyanbola

Admissions tutor