How long is the Diploma in Machine Learning Basics?

Nine to twelve months, on-campus, online or via distance learning. The Diploma in Machine Learning Basics gives every student a cloud GPU sandbox that stays warm between sessions.

Can I take the Diploma in Machine Learning Basics fully online?

Yes. The Diploma in Machine Learning Basics runs fully online with shared notebooks, plus a self-paced distance route. Cohort calls are scheduled twice weekly across UK time zones.

Is the Diploma in Machine Learning Basics recognised by UK employers?

Yes. The Diploma in Machine Learning Basics is a Level 4 UK qualification with content reviewed against BCS data-professional knowledge areas, with a top-up route to the BSc in Data Science.

What are the entry requirements for the Diploma in Machine Learning Basics?

Completed secondary schooling, GCSE English at grade 4 (Maths grade 5 strongly preferred), IELTS 6.0 for international applicants, and a personal statement for the Diploma in Machine Learning Basics.

What does the Diploma in Machine Learning Basics cost?

Fees for the Diploma in Machine Learning Basics vary by mode and domicile. Contact LSCT admissions for the current schedule and short-course bursary or employer-funding options.

Diploma in Machine Learning Basics (UK Level 4) | LSCT | Harold International College of London

Course Overview

The Diploma in Machine Learning Basics at the London School of Commerce and Technology (LSCT) is a 9 to 12 month Level 4 qualification giving students a working, hands-on introduction to machine learning. Sitting in the Information Technology department, the programme is built around the assumption that students need to write code, train and evaluate small models, and explain their results to a non-technical reader by the end of the course — not memorise definitions.

You will work in Python from week one, train your first model in week three, and evaluate a real classification problem against open UK public data sets by mid-cohort. Online, on-campus and distance routes are available from 2026, with shared sandbox infrastructure that lets you keep your work running between sessions.

Industry Context

UK data and ML hiring in 2026 is sharply split between analytics engineers and applied scientists, with junior roles increasingly requiring honest model-evaluation literacy alongside coding fluency. The Diploma in Machine Learning Basics is sequenced against that reality: students are taught data leakage, overfitting and silent failure modes before they are allowed to celebrate a high accuracy number. Tutors include working London ML engineers, and module structure is confirmed at enrolment.

Assessment Approach

Assessment on the Diploma in Machine Learning Basics is portfolio-led: every module produces a checked-in notebook, and the capstone is reviewed by a working ML engineer from a London tech firm. Students leave with a public-or-private GitHub portfolio they can hand to a hiring manager.

Key Features of the Diploma in Machine Learning Basics

Level 4 UK diploma with content reviewed against BCS knowledge areas for the data professional pathway.
Three study modes with cloud GPU sandbox available to every student.
Public data set exercises using ONS, NHS Digital and Transport for London open data.
Model evaluation focus — students leave able to spot leakage, overfitting and silent failure modes.
Capstone notebook reviewed by a working ML engineer from a London tech firm.

What You Will Learn

The diploma is organised around the working loop of a junior ML practitioner: load, clean, model, evaluate, explain. You will graduate able to scope a small ML problem, build a baseline and an improved model, evaluate them honestly against a held-out set, and write a results note your line manager will believe.

Python for data science — NumPy, Pandas and matplotlib
Statistics fundamentals — descriptive statistics, sampling and inference
Supervised learning — regression and classification with scikit-learn
Unsupervised learning — clustering and dimensionality reduction
Model evaluation, cross-validation and metrics
Feature engineering and data leakage
Introduction to neural networks and gradient descent
Reproducibility, notebooks and version control

Who This Course Is For

Students preparing to enter a BSc in Data Science or AI.
Working developers wanting credible ML grounding before a specialist role.
Analysts moving from BI into predictive modelling.
International students aiming for a UK Level 4 with a clear top-up route.

Career Pathways

The diploma is a credible foundation for entry-level data and ML roles, with consistent demand across London tech firms, public-sector analytics and consultancies. Typical first roles include:

Junior Data Analyst (with ML literacy)
ML Engineering Apprentice
Data Engineer (entry-level)
Quantitative Analyst (junior)
Research Assistant (academic / think tank)
QA Engineer with model-testing focus

Most graduates progress directly to the BSc in Data Science or the Higher Diploma in Artificial Intelligence.

Entry Requirements

Completed secondary schooling (A-levels, BTEC Level 3, IB or recognised international equivalent) or equivalent work experience.
GCSE English Language at grade 4/C or above (or equivalent), plus GCSE Mathematics at grade 5/C strongly preferred given the quantitative load.
English language: IELTS 6.0 overall (no band below 5.5) for non-native English speakers.
A short personal statement; mature applicants may apply with a CV and a brief technical chat covering prior Python or statistics exposure.

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. ML students benefit specifically from public-data sets curated with TfL and the ONS that you cannot get cleanly anywhere else.

Why Study the Diploma in Machine Learning Basics at LSCT

The diploma sits inside the LSCT Information Technology department alongside data science, cloud and cyber cohorts, and tutors include working London ML engineers. ML students benefit specifically from public-data sets curated with TfL and the ONS that you cannot get cleanly anywhere else, and module structure is confirmed at enrolment.

Apply for the Diploma in Machine Learning Basics

Ready to take the next step into the Information Technology sector? Click Enrol Now to submit your application for the Diploma in Machine Learning Basics; admissions reply within one working day with sandbox credentials for accepted students.