How long is the MSc in Data Science?

One year full-time on-campus, or up to two years part-time through the online and distance routes — the MSc in Data Science dissertation and model-deployment deadlines are identical across all modes.

Can I study the MSc in Data Science online?

Yes. The MSc in Data Science is offered on-campus near Silicon Roundabout, fully online with live model-review labs, or via distance learning with structured monthly sprints and recordings.

Is the MSc in Data Science recognised in the UK?

The MSc in Data Science is aligned with BCS (The Chartered Institute for IT) accreditation criteria and informed by working London data leads — credentials UK data employers immediately recognise.

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

A UK 2:2 honours degree (or international equivalent) in a numerate subject, IELTS 6.5 for non-native applicants, plus a technical sample for the MSc in Data Science shortlist.

How much does the MSc in Data Science cost?

Tuition for the MSc in Data Science varies by study mode and domicile. Merit scholarships, alumni bursaries and employer-sponsored places are reviewed each intake — contact LSCT admissions.

MSc in Data Science in London in London 2026 | LSCT | Harold International College of London

Course Overview

The MSc in Data Science at LSCT is a one-year postgraduate degree inside the Information Technology department, designed for analysts, software engineers and numerate graduates ready to move into senior data-science and applied machine-learning roles. Taught from our central London base across on-campus, online and distance-learning routes from 2026, the programme combines the statistical and ML foundations of modern data science with the engineering practice (MLOps, observability, deployment) and the UK regulatory environment (ICO AI guidance, the AI Safety Institute, FCA data principles) the role now demands.

You will work on real-style data sets from the start, ship a deployed ML model under monitoring, present at an internal MLOps review and complete a dissertation tied to a UK industry problem. By the end of the MSc in Data Science you will have a public engineering portfolio, an awareness of UK AI assurance, and the language to walk into a senior data-scientist or ML-engineer interview at a UK fintech, healthtech or consultancy.

Key Features

UK postgraduate degree aligned with BCS (The Chartered Institute for IT) accreditation criteria and informed by working London data leads.
MLOps-first delivery — every taught ML project ships to a deployment environment under monitoring, not just to a notebook.
Three study modes — on-campus near Silicon Roundabout, fully online with live model-review labs, or distance learning with structured monthly sprints.
UK AI assurance lab — students score a real-style ML system against ICO AI guidance and the UK AI Playbook.
Module on UK data ethics covering UK GDPR for analysts, fairness audits and the role of the AI Safety Institute.
Industry-linked dissertation with a London data team in fintech, healthtech, retail or research where places are available.

What You Will Learn

The MSc in Data Science runs across three taught semesters plus a dissertation. You will graduate fluent in modern ML, capable of shipping production models and able to defend your work in an internal model-review meeting.

Statistical Foundations and Probabilistic Reasoning
Machine Learning (supervised, unsupervised, reinforcement)
Deep Learning and Modern Architectures
Natural Language Processing and Applied LLMs
Data Engineering Foundations (SQL, dbt, warehouses)
MLOps and Production ML
Causal Inference and A/B Testing
UK Data Ethics and AI Assurance (ICO, AI Safety Institute)
Research Methods and Dissertation

The teaching pattern is intentionally practitioner-led. Each module pairs taught content with at least one hands-on lab — real tooling, real data, real code review — and you are expected to push pull requests, write incident reports and defend technical decisions in code review. That working rhythm gives our graduates the day-one credibility UK engineering, security and data employers want, and is part of why so many of our students take offers before they finish.

Who This Course Is For

Analysts, junior data scientists and BI specialists stepping up to data-science and ML roles.
Software engineers and quants moving into applied ML positions.
Numerate graduates (maths, physics, statistics, economics) entering UK data careers.
International applicants targeting UK Skilled Worker visa-eligible data-science roles requiring a recognised Master's.

Career Pathways

MSc graduates step into the data-science and ML pipelines of UK fintech, healthtech, retail tech, the public sector and the major UK consultancies. The MSc in Data Science is calibrated to make you delivery-ready on a real ML problem within weeks. Typical graduate roles include:

Data Scientist (UK fintech, healthtech, retail)
Machine Learning Engineer
Applied Scientist (research-adjacent)
Data Engineer (ML platform crossover)
Analytics Consultant (Big Four or boutique)
AI Assurance Analyst (regulator, consultancy)

The MSc also serves as a strong foundation for PhD study in machine learning, applied statistics or AI safety.

You will also build the network that underpins UK technology careers: an alumni community across fintech, healthtech, retail tech and the public-sector engineering teams, a working tutor team drawn from current production engineering, and an annual industry careers afternoon at which UK technology hiring managers take CVs and book follow-up conversations with current students.

Entry Requirements

A UK 2:2 honours degree (or international equivalent) in a numerate subject (computer science, mathematics, statistics, physics, engineering, economics or related disciplines).
Applicants from non-cognate fields may apply with five years' senior professional experience in analytics, software engineering or quantitative roles.
IELTS 6.5 overall (no band below 6.0) for non-native English speakers.
A personal statement, two references and a short technical sample (a Kaggle notebook, GitHub repo or deployed model) demonstrating practical aptitude.

Across the programme you also sit alongside working engineers, security analysts and product leads in regular guest sessions — practitioners from the City, Old Street and King's Cross who walk you through what real production systems, real incident reviews and real engineering interviews look like. The London tech labour market moves quickly, and our syllabus is reviewed annually to keep pace with the tools and patterns UK employers actually hire on.

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. For data-science students that proximity matters: the AI Safety Institute, the major UK fintech and healthtech data teams and the consultancy ML practices all sit within tube reach of our seminar rooms.

Our graduates work across the UK technology economy — fintech, healthtech, retail tech, the Government Digital Service, the consulting houses and the consumer-app teams that define London's product cluster. LSCT's employability team keeps an annual employer map current and runs portfolio-review evenings attended by working hiring managers from the major UK product, engineering and security teams.

Apply for MSc in Data Science

Specialise at postgraduate level with the MSc in Data Science. Click Enrol Now to apply; admissions teams reply within one working day with scholarship and funding guidance, including a personalised review of your technical sample before interview.