How long does the BSc in Machine Learning take to complete?

The BSc in Machine Learning runs for three years full-time, with part-time and accelerated routes available. A year-two placement at a London ML or data team is built in.

Can I take the BSc in Machine Learning fully online?

Yes. The BSc in Machine Learning is offered on-campus near King's Cross, fully online with live notebook labs and remote GPU access, or as distance learning with weekly deadlines.

Is the BSc in Machine Learning recognised by UK employers?

Yes. The BSc in Machine Learning is a UK-accredited honours degree aligned with BCS standards, and graduates enter applied ML roles at London fintechs, healthtechs and product companies.

What are the entry requirements for the BSc in Machine Learning?

Applicants to the BSc in Machine Learning need three A-levels at BBC or equivalent including Maths, GCSE English at grade 5 and Maths at grade 5, plus IELTS 6.5 for international students.

What does the BSc in Machine Learning cost and are scholarships available?

Tuition for the BSc in Machine Learning varies by route and domicile. Quantitative-aptitude and means-tested scholarships are reviewed each intake — contact LSCT admissions for details.

BSc in Machine Learning — UK Honours Degree | LSCT | Harold International College of London

Course Overview

The BSc in Machine Learning at the London School of Commerce and Technology (LSCT) is a three-year undergraduate honours degree (part-time and accelerated routes available) designed for students entering applied machine-learning engineering, MLOps and data-science roles across UK industry from 2026. It is taught on-campus near the King's Cross tech corridor, fully online with live notebook labs, and through structured distance learning.

You will work in Python from week one and ship a deployed model by the end of year one. By graduation you will have built and evaluated supervised, unsupervised and deep-learning systems, taken a model from notebook to a live endpoint, and defended your evaluation against a real-world data-drift scenario.

The UK machine-learning labour market has matured fast since the ICO published its guidance on AI and data protection and the EU AI Act began rippling into UK product decisions. London fintech, ad tech and healthtech now want ML engineers who can both train a model and reason about model risk, evaluation and deployment hygiene — not only finish a Kaggle notebook. The BSc in Machine Learning is sequenced against that brief.

Key Features of the BSc in Machine Learning

BCS- and AWS-aligned curriculum covering the practitioner stack — Python, PyTorch and cloud ML.
Three study modes — on-campus near King's Cross, fully online with live notebook labs, or distance learning with weekly model deadlines.
GPU lab access for deep-learning coursework and final-year capstone.
MLOps module — taking a model from notebook to production with monitoring and rollback.
Year-two placement with a London product company, fintech or NHS digital data team.
Final-year capstone — a deployed model with a written evaluation and a model card.
Responsible-AI strand — UK ICO guidance, fairness metrics and documentation patterns assessed inside every applied module.

What You Will Learn on the BSc in Machine Learning

The degree is structured around three layers — mathematics, models and production — repeated across years and rising in complexity. You will graduate able to derive gradient descent on paper, train a deep network on a GPU, and ship that model behind an authenticated API.

Mathematics for machine learning — linear algebra, calculus, probability and statistics.
Python engineering — clean code, testing and reproducible notebooks.
Classical machine learning — regression, trees, ensembles and SVMs.
Deep learning — feed-forward, convolutional and transformer architectures in PyTorch.
Natural language processing and computer vision applied projects.
Model evaluation, fairness and the UK ICO AI guidance.
MLOps — feature stores, training pipelines and model monitoring.
Capstone — a deployed model with a written model card and post-launch monitoring plan.

Coursework is portfolio-led. Every applied module produces a tested notebook, a written technical report and a recorded model walkthrough — together these form an interview portfolio that graduates take into UK ML hiring loops. Assessment combines short technical write-ups, mid-programme code review against a panel of working London ML engineers, and a final capstone defence in the format used by product-company hiring panels.

Industry Context and Assessment Approach

The BSc in Machine Learning is taught by working ML engineers, data scientists and applied researchers drawn from London's product and consulting market. Cohorts run a fortnightly paper-reading club at which a current arXiv preprint is dissected by both staff and senior students — a habit graduates report carries straight into their first jobs. Each year ends with a model-risk review modelled on the FCA's expectations of model governance in regulated firms; students learn to write the documentation a model-risk team actually accepts, not only the training loop.

Who This Course Is For

School leavers with strong maths who want a UK ML engineering degree.
Self-taught data enthusiasts ready to convert notebooks into shipped products.
Career changers from engineering, physics or quantitative finance moving into ML.
International students seeking a UK-recognised machine-learning degree near the tech corridor.
Returners to work re-entering UK technology after a career break who want a refreshed credential.

Career Pathways

LSCT machine-learning graduates enter applied ML and data roles across London fintech, ad tech, healthtech and the public sector. Many continue on the placement employer's graduate scheme; others move into postgraduate research in machine learning, data science or AI ethics.

Junior Machine Learning Engineer
Data Engineer
Data Scientist (junior)
MLOps Engineer
Computer Vision Engineer (junior)
Applied AI Researcher (post-internship)

The BSc is also a recognised foundation for an MSc in machine learning, data science or AI safety, and feeds directly into LSCT's postgraduate IT programmes.

Entry Requirements

Three A-levels at grades BBC or above, including Maths or a strong quantitative subject (or equivalent IB 28+, BTEC DMM).
GCSE English Language at grade 5/C and Mathematics at grade 5/C (or equivalent); a maths aptitude task is set at interview.
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 and short interview.

Why Study the BSc in Machine Learning 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.

Apply for the BSc in Machine Learning

The BSc in Machine Learning 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 intake dates and entry-route guidance.