How long is the BSc in Data Science?

Three years full-time on-campus, with part-time and accelerated online routes. The BSc in Data Science extends to four years with the optional placement year in a London tech firm or public-sector data team.

Can the BSc in Data Science be studied online?

Yes. The BSc in Data Science runs synchronous cohort sessions online across UK and APAC time zones, with shared cloud GPU sandbox, plus a self-paced distance-learning route.

Is the BSc in Data Science recognised by UK employers?

Yes. The BSc in Data Science is a UK-accredited honours degree with content reviewed against BCS data professional knowledge areas and Royal Statistical Society standards, with capstone defence before working data scientists.

What are the entry requirements for the BSc in Data Science?

BBC at A-level including Maths (or IB 28 with HL Maths), GCSE English at grade 5 and Maths at grade 6, plus IELTS 6.5 for international applicants. Strong numeracy is essential for the BSc in Data Science.

What does the BSc in Data Science cost?

Tuition for the BSc in Data Science varies by route and domicile, with cloud GPU credits and software vouchers included. Contact LSCT admissions for the current schedule and scholarship eligibility.

BSc in Data Science — UK Honours (Online, London) | LSCT | Harold International College of London

Course Overview

The BSc in Data Science at the London School of Commerce and Technology (LSCT) is a three-year undergraduate degree producing graduates fluent across the working data-science stack: statistics, Python, modern ML, data engineering basics and the communication discipline that turns models into decisions. Sitting in the Information Technology department, the BSc treats data science as an engineering practice first and a research practice second.

You will work with real (anonymised) UK data from week one, complete a placement option in year two with a London tech firm or public-sector data team, and produce a defended capstone project deployed to a public-facing service. Online, on-campus and distance routes are available from 2026.

Industry Context for the BSc in Data Science

UK data-science hiring in 2026 has settled around a clear preference for engineers who can ship, evaluate and explain a working model rather than only build one. The Royal Statistical Society's calls for honest reporting have moved into mainstream practice, the Information Commissioner's Office has tightened its position on automated decision-making, and the Government Digital Service's data-engineering principles now drive how the public sector hires. The BSc in Data Science is sequenced against this reality, with statistical honesty, reproducibility and clean explanation built into every module rather than added at the end.

Key Features

UK-accredited BSc honours degree with content reviewed against BCS data professional knowledge areas and Royal Statistical Society standards.
Three study modes with shared cloud GPU sandbox and synchronous cohort sessions across UK and APAC time zones.
Placement year option with a London public-sector data team or fintech.
UK public-data emphasis — projects use ONS, NHS Digital, TfL and DfE open data.
Reproducibility module — every capstone ships with a runnable repo and clean README.
Capstone deployed as a public service and defended in viva before a working data scientist.

What You Will Learn

The degree organises data science into four working strands: statistical reasoning, programming and engineering, modelling and inference, and communication. You will graduate able to design a small experiment, write production-grade Python, build and evaluate a model honestly, and explain the result to a sceptical commissioner.

Statistical reasoning and probability
Python for data science and software engineering practice
Data wrangling, SQL and modern data tooling
Supervised and unsupervised machine learning
Deep learning fundamentals
Causal inference and experiment design
Data engineering and pipeline basics
Data ethics, ICO guidance and responsible deployment
Communicating uncertainty to non-technical audiences

Who This Course Is For

A-level leavers targeting a UK data-science or ML engineer career.
International students wanting a UK BSc with strong applied output.
Working analysts wanting an honours degree with engineering depth.
Career switchers from maths or science backgrounds entering tech.

Career Pathways

Graduates work across UK product companies, scale-ups, public-sector data teams and consultancies, with consistent demand from City fintech and the King's Cross data corridor. Typical destinations include:

Data Scientist (junior to mid)
Data Engineer
ML Engineer (entry level)
Analytics Engineer
Quantitative Analyst (junior)
Business Analyst with data specialism

The degree articulates into an MSc in Data Science, Statistics or Artificial Intelligence. Graduates typically progress into junior data-science and analytics-engineering roles within months of completion, with London-based junior data-scientist salaries sitting in the upper band of the technology graduate market and progression accelerating once a defended capstone artefact and reproducible repo are held.

Assessment Approach for the BSc in Data Science

The BSc in Data Science is assessed through statistical workbooks, code submissions evaluated against passing tests, written modelling memos and a final capstone defence. Year one focuses on derivations, foundational Python and small experiments; year two on real data wrangling, supervised learning and the placement option; year three on a deployed capstone, an honest evaluation report and a viva defence before a working data scientist. Each artefact is marked against a written rubric drawn from BCS data-professional knowledge areas and Royal Statistical Society reporting standards, so students leave with documents employers can read on first sight.

Entry Requirements

Three A-levels at grades BBC or above (Mathematics required at A-level or strong equivalent), or an equivalent UK / international qualification (IB 28+ with HL Maths, BTEC DMM with maths track, Foundation Year pass).
GCSE English Language at grade 5/C and Mathematics at grade 6/B (or equivalent) — strong maths is essential.
IELTS 6.5 overall (no band below 6.0) for non-native English speakers.
A personal statement; mature applicants (21+) may apply with a portfolio of analysis work and a short interview.

Why Study at LSCT

The London School of Commerce and Technology (LSCT) is a specialist higher-education provider based in central London and part of Harold International College. We teach in small cohorts so every student is visible to their tutor, run a single intake schedule that students can rely on, and partner with UK professional bodies so qualifications carry weight with employers. London puts Whitehall, the City, Silicon Roundabout, the Royal Courts of Justice, the West End and the NHS estate within a short tube ride of every classroom — and our students use that proximity in their projects, placements and graduate job hunts. Data-science students get placements at public-sector data teams across Whitehall as well as City fintechs.

Apply for the BSc in Data Science

The BSc in Data Science is built to launch your career in the Information Technology sector. Click Enrol Now to submit your application; admissions reply within one working day with sandbox-credential guidance for accepted students.