How long does the Diploma in Machine Learning take?

The Diploma in Machine Learning runs nine to twelve months. The Diploma in Machine Learning uses a modular calendar so working analysts can pace themselves.

How is the Diploma in Machine Learning delivered?

The Diploma in Machine Learning is delivered on-campus in London, fully online with GPU access, or by distance learning. All three routes share the same weekly seminar cohort.

Is this Diploma recognised in the UK?

Yes. The Diploma in Machine Learning is a UK Level 4 qualification aligned with BCS Foundation topics and Institute of Analytics practitioner themes.

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

You need a Certificate, A-levels or two years of relevant analytics or software experience. IELTS 5.5 overall is required for non-native English speakers.

What are the fees and funding options?

Fees for the Diploma in Machine Learning are quoted per intake and include instalment plans. LSCE admissions reviews employer sponsorship and scholarships at application.

Diploma in Machine Learning | LSCE | Harold International College of London

Course Overview

The Diploma in Machine Learning is a UK Level 4 qualification lasting nine to twelve months covering practitioner-grade competence in supervised, unsupervised and applied deep learning. The programme concentrates on Python, scikit-learn, PyTorch or TensorFlow, feature engineering pipelines, model evaluation and reproducible experimentation, and the syllabus is aligned with BCS (The Chartered Institute for IT) guidance and reference materials from Institute of Analytics (IoA). Delivery is available on-campus in central London, fully online with the same lab and tooling provisioning, or by distance learning, and every route joins the same intake cohort with weekly tutor visibility and named programme-tutor support.

By graduation from the Diploma in Machine Learning you will be a working ML practitioner able to ship supervised models responsibly, with practitioner foundations that map to junior technical roles demonstrated through a portfolio of coursework, applied labs and, at the closing stage, a blend of coursework, applied labs and short applied examinations. Every learner leaves the Diploma in Machine Learning with a documented body of work suitable for UK employer conversations across analytics consultancies, product-team ML groups and public-sector data science teams, and with a clear progression route into the next step of the LSCE ladder. Coursework is scheduled around working professionals so that part-time and full-time routes share the same weekly seminar, the same assessment rubric and the same tutor group.

Key Features

Cohort teaching in small tutor-visible groups at the LSCE central London campus, online, or by distance learning.
Curriculum aligned with BCS (The Chartered Institute for IT) guidance and referenced against Institute of Analytics (IoA) and Royal Statistical Society (RSS) materials.
Applied labs covering Python, scikit-learn, PyTorch or TensorFlow, feature engineering pipelines, model evaluation and reproducible experimentation.
Weekly clinic sessions where tutors work through problem sets, code review or design critique with you on your own coursework.
Assessment structured as a blend of coursework, applied labs and short applied examinations rather than a single high-stakes final paper, so progress is visible throughout the Diploma in Machine Learning.
Careers-service introductions to London employers active in analytics consultancies, product-team ML groups and public-sector data science teams, with dedicated CV and portfolio review sessions.
Structured articulation route within the LSCE ladder from a UK Level 4 qualification lasting nine to twelve months into the next level of study or straight into employment.

What You Will Learn

Build supervised learning pipelines with scikit-learn and PyTorch.
Engineer features from tabular, text and image data.
Evaluate models with appropriate metrics and error analysis.
Manage experiments with reproducible tooling and version control.
Deploy models behind APIs with monitoring and rollback plans.
Apply fairness, bias and explainability checks to shipped models.
Practise cross-validation, resampling and model-selection discipline.
Document ML work for review and audit by non-specialists.

Who This Course Is For

A-level and Certificate progressors moving into a first practitioner role in machine learning.
Working staff formalising two or more years of related workplace experience.
Career changers who have completed a related Certificate at LSCE or elsewhere.
International applicants seeking a UK Level 4 credential in machine learning.
Professionals sponsored by an employer to embed the Diploma in Machine Learning coursework in a live estate.

Career Pathways

BI Analyst assistant
Blockchain Developer assistant
IoT Solutions Engineer assistant
Predictive Analytics Consultant assistant
AI Governance Officer assistant
AI Engineer assistant
Machine Learning Engineer assistant

The LSCE careers service supports Diploma in Machine Learning graduates with structured CV clinics, portfolio and mock-interview sessions and named introductions to hiring managers across analytics consultancies, product-team ML groups and public-sector data science teams. Every student meets a named careers adviser in the final stage, and alumni continue to receive careers coaching, job-alert access and application review after graduation. Where the Diploma in Machine Learning offers a placement or capstone with an employer sponsor, the careers team helps you shape that engagement into a portfolio entry recruiters can validate.

Entry Requirements

A relevant Certificate, A-levels (or equivalent), or two years of relevant employment.
GCSE English at grade 4/C and Mathematics at grade 4/C (or equivalent).
IELTS 5.5 overall (no band below 5.0) for non-native English speakers.
One academic or professional reference.
Short statement of intent with a paragraph on career direction.

Why Study at LSCE

The London School of Computing and Engineering is a specialist division of Harold International College of London teaching in small, tutor-visible cohorts. LSCE partners with UK professional bodies including BCS (The Chartered Institute for IT), and central London places the Alan Turing Institute, the NCSC, the ICE, IMechE and IET, and the City's engineering and technology employers within a short tube ride of every classroom.

Every intake, on-campus or remote, joins the same weekly seminar structure with named programme-tutor support. Three parallel study modes let A-level leavers, Certificate progressors and experienced staff complete the Diploma in Machine Learning without leaving employment, and the LSCE careers service runs at least one industry-careers day each academic year to connect students with employers active in analytics consultancies, product-team ML groups and public-sector data science teams. Curriculum alignment is refreshed each year against BCS (The Chartered Institute for IT) and Institute of Analytics (IoA) guidance so that graduates leave with a syllabus that reflects current UK sector expectations.

Apply for Diploma in Machine Learning

Start your Level 4 qualification with LSCE. Click Enrol Now, admissions will respond within one working day with intake dates and credit-transfer guidance. Rolling intake dates mean early applications receive the widest choice of tutors, elective modules and supporting information, and international applicants are supported through visa, accommodation and English-language guidance in the same first response. Enrol Now