How long is the MSc in Data Science?

The MSc in Data Science runs one year full-time or two years part-time at UK Level 7, closing with a dissertation or sponsor consulting project.

Can I study the MSc in Data Science online?

Yes. The MSc in Data Science is delivered on-campus, fully online with provisioned GPU access and by distance learning, all sharing the same cohort and named supervisor.

Is the MSc recognised in the UK?

The MSc in Data Science is a UK Level 7 postgraduate degree aligned with RSS, the Institute of Analytics and the Alan Turing Institute research agenda, giving credible senior-track evidence to UK employers.

What are the entry requirements?

You need a UK 2:2 Bachelor's in a relevant discipline, or five or more years of senior professional experience for admission by portfolio. International applicants need IELTS 6.5 overall.

What are fees and funding options?

Fees for the MSc in Data Science are published on the LSCE course page and vary by mode. Admissions can confirm instalment options and current scholarship review.

MSc in Data Science | LSCE | Harold International College of London

Course Overview

The MSc in Data Science is a UK Level 7 postgraduate degree qualification running one year full-time or two years part-time, aligned with UK AI Safety Institute and Alan Turing Institute reference material and Royal Statistical Society professional standards. It is designed for data professionals and senior developers moving into research-informed applied data-science practice, closing with a substantial dissertation or sponsor consulting project, and the curriculum is refreshed each year against UK sector expectations and the London data and AI ecosystem. Every module is written and marked to UK postgraduate standards, and the same intake cohort covers on-campus, fully online and distance-learning routes with weekly tutor visibility across every mode. Assessment briefings, taught sessions and tutor clinics run to a single teaching rhythm, and the MSc in Data Science schedule is published at the start of each intake so learners can plan around work, family and travel commitments.

By the closing weeks of the MSc in Data Science you will design defensible experiments, deliver applied data-science projects end to end, evaluate models against business criteria and defend a dissertation in front of an academic panel, and be ready to step into senior, consulting or research-adjacent UK positions. The programme sits alongside the Alan Turing Institute, the UK AI Safety Institute and the fintech, medtech and public-service data teams that recruit heavily from London-based programmes, so the professional-body scene you are studying sits inside a short tube ride of the central London campus. Assessment blends taught coursework, applied artefacts and a closing dissertation or sponsor consulting project moderated to UK postgraduate standards, with a named programme tutor from induction through the closing submission. Every learner receives structured milestone feedback, one-to-one review sessions and an evidence-based portfolio review that maps directly onto UK employer expectations for the MSc in Data Science subject area.

Key Features

Curriculum aligned with Institute of Analytics and Royal Statistical Society competencies.
Modules on advanced statistical modelling, machine learning and MLOps.
Applied projects using Python, R, PyTorch and cloud managed data-science services.
Choice of research dissertation or sponsor consulting project.
Named dissertation supervisor and structured milestone reviews.
Guest sessions from Alan Turing Institute and Royal Statistical Society community.
Careers-service introductions to London data-science and fintech employers.

What You Will Learn

Design defensible experiments and observational studies against UK data.
Apply advanced statistical modelling to structured and unstructured datasets.
Build supervised, unsupervised and reinforcement-learning models with rigour.
Evaluate models with domain-specific error analysis and business framing.
Design MLOps pipelines that support reproducibility and model governance.
Communicate insights to executive stakeholders with clarity and calibration.
Apply research methodology to a piece of original data-science work.
Defend a dissertation or consulting project in a formal viva.

Who This Course Is For

Bachelor graduates progressing into senior data-science roles.
Working data analysts stepping into applied data-science positions.
Career changers with adjacent numerate degrees.
Experience-route applicants with five or more years of senior professional practice.
International applicants aligning senior experience with UK academic vocabulary.

Career Pathways

MLOps Engineer
Data Science Team Lead
Head of Analytics (with progression)
Senior Data Scientist
Machine Learning Engineer
Applied AI Researcher
Predictive Analytics Consultant

The LSCE careers service runs one-to-one interview support in the final stage and taps its UK contact book across financial services, health-tech and public-service data teams to help place MSc graduates into senior UK positions. Alumni support continues after graduation through the LSCE careers network, so the MSc in Data Science remains a live credential in your career progression conversations for years after you finish.

Entry Requirements

Applicants to the MSc in Data Science are assessed on the balance of academic preparation, professional experience and stated intent to work in senior data science and applied analytics. The requirements below are the standard published entry criteria, and admissions will confirm any credit-transfer, English-language or portfolio route in the first response.

A UK Bachelor's degree at 2:2 or above, or an international equivalent, in a discipline relevant to data science.
Applicants with five or more years of senior professional experience are considered for admission by portfolio.
IELTS 6.5 overall (no band below 6.0) for non-native English speakers.
Two references , normally academic; senior professional accepted for experience-route applicants.
A one-page personal statement setting out your dissertation or capstone interest in data science.

Why Study at LSCE

LSCE is the specialist computing and engineering division of Harold International College of London, teaching in small tutor-visible cohorts across every level of the ladder. The central London campus places the Alan Turing Institute at the British Library, the UK AI Safety Institute and the fintech and medtech data teams of the City within a short tube ride, so students learning on the MSc in Data Science can attend the same industry evenings, guest lectures and continuing professional development sessions that working practitioners attend. Partnerships with UK professional bodies, including the ones woven through the MSc in Data Science curriculum, mean the qualification carries weight with employers, and the syllabus is refreshed each year against professional-body guidance and the latest UK sector needs.

On-campus, fully online and distance-learning routes join the same intake cohort with weekly tutor visibility, so the postgraduate experience of the MSc in Data Science does not depend on which route you pick. Students routinely attend PyData London, London AI meetups, the Royal Statistical Society local groups and the BCS Data Management Specialist Group during their studies, and the LSCE careers service maintains a working contact book across UK employers, hosts industry-careers days and offers one-to-one application support during your final stage. Postgraduate learners on the LSCE ladder also access shared library, elective-module and student-society facilities through the wider Harold International College network subject to availability.

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