BSc (Hons) Data Science and Artificial Intelligence

Course overview

Develops programming, mathematics, databases, software engineering, data science and artificial intelligence skills through practical and applied learning.

Course details

Degree level

Bachelor's

Subject

Data Science / AI

Duration

Three years

Intake

January 2027

Tuition fee

£16,275 / yearUniversity fee information (opens in a new tab)

Initial deposit

95% for CAS issuance

City

London

Country

England

Campus

UWS London Campus

About this information

The details on this page have not yet been checked against the official course page by our team. Fees, intakes and requirements can change, so always confirm them on the official course page before you apply.

Not recorded here yet: Pakistan-specific requirements.

English Language Requirements

Main English Requirements

Alternative English Requirements

Only the tests listed here are shown as accepted for this course.

Entry requirements

General entry requirements

Year 1: normally 90 UCAS Tariff points including Mathematics, Applications of Mathematics or Computing. Examples: Scottish Highers BCCC; A Levels CCD including Mathematics or Computing (and Mathematics or Computing at GCSE). Year 2: Scottish Advanced Highers CCD including Computing/Maths; A Levels BBC including Computing/Maths; T Level Grade M in relevant subject; IB 28 including Computing/Maths; plus specified HNC/BTEC routes.

Scholarships & discounts

For selected programmes at UWS Scottish and London campuses: • Class-based programmes: net fee £13,000 • Lab-based programmes: net fee £15,000

Pre-CAS interview

Required

Yes — a Pre-CAS / credibility interview is part of the process

Stage

Before the CAS is issued

Format

Credibility interview

Course modules

• 480 credits over four years. Level 7: Introduction to Programming; Introduction to Software Engineering; Database Systems; Applied Mathematics; Analysis of Data; ASPIRE. Level 8: Intermediate Programming; Introduction to Network and Cloud Computing; Software Engineering Practice; Data Structures and Algorithms; ASPIRE 2; Probability and Statistics. Level 9: Research Methods in Computing; Professional Computing Practice; DevOps; Mathematics for Data Science; Fundamentals of Data Science; Data Visualisation, with optional Algorithms and Collections, Cloud Services and Architectures, Statistical Estimation and Inference. Level 10: Computing Honours Project; Data Engineering; Artificial Intelligence Applications; Big Data, with optional Advanced Machine Learning or Decision Support Systems.