Course overview
Learn to turn complex data into reliable insight and practical decisions.
Develop the programming, mathematical and analytical expertise to collect, manage and interpret data, then apply statistics, artificial intelligence and machine learning to practical business and technology problems.
Year One
Build foundations in programming, data analysis, information systems, financial mathematics, logic and mathematical techniques.
Year Two
Progress into data engineering, data analytics, databases, programming with data, statistical modelling and the ethical responsibilities of computing professionals.
Year Three
Apply artificial intelligence, machine learning, big data, web development and project analysis while completing an independent 30-credit project.
Blended learning
Combine online and on-campus study through daytime or evening/weekend timetables, supported by lectures, tutorials, workshops and practical computer-lab sessions.
Curriculum
Three years from computing fundamentals to applied artificial intelligence and a final project.
01Year 1
Level 4
120 credits
Year 1
Level 4
- Data Analysis15 credits
- Financial Mathematics15 credits
- Fundamentals of Computing15 credits
- Introduction to Information Systems15 credits
- Logic and Mathematical Techniques30 credits
- Programming30 credits
02Year 2
Level 5
120 credits
Year 2
Level 5
- Data Engineering15 credits
- Programming with Data15 credits
- Data Analytics15 credits
- Databases15 credits
- Professional and Ethical Issues15 credits
- Smart Data Discovery15 credits
- Statistical Methods and Modelling Markets30 credits
03Year 3
Level 6
120 credits
Year 3
Level 6
- Artificial Intelligence and Machine Learning15 credits
- Career Development Learning15 credits
- Data and Web Development30 credits
- Artificial Intelligence and Big Data in Business15 credits
- Project Analysis and Practice15 credits
- Project30 credits
Module availability and content may change as part of the provider’s ongoing academic review.
Assessment
Practical ways to show what you know.
Teaching uses lectures, tutorials, workshops and practical computer-laboratory sessions.
Assessment includes coursework, in-class tests, quizzes, multiple-choice tests and unseen examinations.
The final project integrates data-science theory, professional practice, investigation and practical technical delivery.
Entry requirements
Your route onto the course.
Academic requirements
- 96 UCAS points.
- GCSE Mathematics grade 4/C, an accepted equivalent or a successful university mathematics assessment.
- Applicants with relevant experience who do not meet the standard requirements may be considered individually and invited to an academic interview.
English language
- GCSE English grade 4/C or an accepted equivalent.
- IELTS 5.5 with no component below 5.5, or an accepted equivalent.
Interview
Applicants may be invited to an admissions interview about their motivation or an academic interview to assess subject readiness where standard requirements are not met or they have been out of education for some time.
Application documents
- Passport personal-details page.
- Qualification certificates and transcripts, with certified translations where required.
- A personal statement of more than 250 words where requested.
- A CV where requested.
Student visa sponsorship
The university centres currently state that they cannot sponsor international students for this programme. Applicants requiring Student visa sponsorship should confirm alternative eligible programmes directly with the university before applying.
Fees & funding
Understand the full cost.
Annual fees may increase in line with inflation and government guidance.
Tuition covers teaching, access to resources, registration and student support services. It does not include optional books, stationery, printing, accommodation, living costs, travel or leisure activities.
The course information recommends allowing approximately £200 per year for optional course texts.
Access to a laptop or desktop computer with a microphone, speakers, webcam and reliable internet connection is required for live online sessions and assignments.
Funding your study
Eligible UK students may be able to receive government Student Finance support towards tuition and living costs.
Eligibility depends on personal circumstances, previous study, the course and the provider.
What you’ll achieve
Skills for ideas that move forward.
Develop a practical command of programming, databases, data engineering, analytics, statistics, artificial intelligence and machine learning.
Evaluate data responsibly, communicate evidence and complete an independent project that addresses a substantial data-science problem.
Career opportunities
Where this course can take you.
Career outcomes depend on your experience, further training and the requirements of each role.
Data analysis
- Data analyst
- Associate data analyst
- Business intelligence analyst
Data science
- Data scientist
- Data science operations officer
- Junior machine-learning specialist
Data engineering
- Data engineer
- Database developer
- Analytics engineering support
Digital projects
- Data project assistant
- Technical analyst
- Machine-learning project support
Frequently asked questions
Course questions.
What is the difference from the foundation-year version?
This three-year route begins directly at Level 4. The four-year version first develops mathematics, programming, cyber-security and connected-technology foundations at Level 3.
Do I need my own computer?
Yes. The published course information requires access to a suitable laptop or desktop computer, webcam, microphone, speakers and reliable internet connection.
How is the course assessed?
Assessment combines coursework and practical activity with in-class tests, quizzes, multiple-choice tests and unseen examinations.