BSc (Hons) Data Science with Foundation Year

Build a strong foundation in mathematics, computing, and analytics to launch your career in the data-driven world.

Programme Overview

The BSc (Hons) Data Science with Foundation Year is designed for students who wish to develop the skills, knowledge, and confidence required to progress into one of the fastest-growing fields globally. The foundation year provides essential grounding in mathematics, computing, and academic skills, enabling progression to the full undergraduate degree.

Over the course of the programme, students will gain expertise in data science, artificial intelligence (AI), statistical modelling, machine learning, and big data technologies. This programme is structured to prepare graduates for employment in industries where data analysis and evidence-based decision-making are critical, as well as for further postgraduate study.

Who is this programme for?

Students who do not currently meet the entry requirements for direct entry to a computing or data-related degree.

Individuals seeking to develop a career in data analytics, machine learning, or AI-related fields.

Professionals and career changers who wish to gain an industry-relevant qualification in data science.

Programme Structure
Foundation Year (Level 3)

• Academic and Professional Skills
• Introduction to Computing and IT
• Foundations of Mathematics for Data Science
• Study and Digital Literacy Skills

Year 1 (Level 4)

Introduction to Data Science

• Programming Fundamentals (Python, R)
• Mathematics and Statistics for Data
• Databases and Information Systems

Year 2 (Level 5)

• Machine Learning and AI Applications
• Data Visualisation and Analytics
• Big Data Technologies
• Research Methods for Computing

Year 3 (Level 6)

• Advanced Machine Learning and Deep Learning
• Cloud Computing and Data Security
• Applied Data Science Project (Independent Study)
• Professional Practice and Industry Applications

Delivery and Learning Approach

Students will benefit from a combination of lectures, seminars, and laboratory sessions with a strong emphasis on applied, practical work. The programme incorporates:

• Hands-on training with programming languages and software tools (Python, R, SQL, and cloud platforms).
• Case studies and real-world datasets from a range of industries.
• Research and independent study supported by experienced academic and industry professionals.
• Opportunities for collaborative projects to simulate workplace environments.

Entry Requirements
Academic Route:

• 48 UCAS points (from A-Levels, BTEC, or equivalent).
• GCSE English and Mathematics at grade C/4 or above (or equivalent qualifications).

Professional/Experience Route:

Applicants with relevant work experience in IT, computing, mathematics, or data-related roles may be considered, subject to assessment.

What You Will Achieve

By the end of the programme, graduates will:

• Demonstrate proficiency in programming languages such as Python, R, and SQL.
• Apply statistical and mathematical techniques to real-world problems.
• Design and implement machine learning and AI solutions.
• Manage, analyse, and visualise large datasets using modern big data tools.
• Critically evaluate the ethical, legal, and security issues surrounding data use.
• Develop transferable skills in problem-solving, project management, research, and communication.

Career Progression

Graduates of this programme will be well-positioned for roles such as:

• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Business Intelligence Analyst
• AI Solutions Developer
• Cloud and Data Security Specialist

Graduates may also progress to postgraduate study, including MSc programmes in Data Science, Artificial Intelligence, Cyber Security, or related fields.

Why Choose This Programme?

• Curriculum designed in line with current industry needs, ensuring high graduate employability.
• A strong balance of theory and practice, preparing students to apply learning directly in the workplace.
• A foundation year that supports students from non-traditional or diverse educational backgrounds.
• Opportunities to work on independent research projects with real-world impact.

Multiple intake options, enabling flexible progression into higher education.