How long is the BSc in Intelligent Systems Engineering?

The BSc in Intelligent Systems Engineering is a three-year UK Level 6 honours degree, with part-time and accelerated routes and a year-two placement at LSCE.

How is the BSc in Intelligent Systems Engineering delivered?

The BSc in Intelligent Systems Engineering is delivered on-campus in central London, online with GPU lab provisioning, or by distance learning, with weekly tutor visibility.

Is the BSc in Intelligent Systems Engineering recognised in the UK?

Yes. The BSc in Intelligent Systems Engineering sits at UK Level 6 and is aligned with BCS, the Institute of Analytics and Alan Turing Institute engagement material.

What are the entry requirements?

You need 96 UCAS points including a relevant subject, GCSE English and Maths, and IELTS 6.0 for non-native speakers. BTEC and Foundation Year students articulate into the BSc in Intelligent Systems Engineering.

How much does the BSc in Intelligent Systems Engineering cost?

Fees for the BSc in Intelligent Systems Engineering follow UK Level 6 bands. Scholarship review, instalment plans and employer-sponsored routes are available, and admissions confirms figures within one working day.

BSc in Intelligent Systems Engineering | LSCE | Harold International College of London

Course Overview

The BSc in Intelligent Systems Engineering is a UK Level 6 honours degree running three years full-time, with part-time and accelerated routes. It combines AI, control and systems engineering so graduates can design intelligent products end to end, from sensor and actuator layer through learning-based decision-making. The syllabus is aligned with BCS, Institute of Analytics and Alan Turing Institute engagement material.

By graduation you will be prototyping intelligent systems, delivering a year-two industry placement and closing with a final-year capstone on a real intelligent-systems brief.

UK applied AI practice is shaped by the Alan Turing Institute research community, UK AI Safety Institute engagement material and everyday employer pressure to deploy responsibly on real data.

The BSc or BEng assessment model uses coursework, exams, placement performance and a final-year project. Marks are moderated internally and externally to UK honours-degree standards.

Undergraduate cohorts study through a mix of lectures, seminars, labs and studio-format critique. Every year is structured around clear progression signals so students always know where they stand against the honours-degree standard.

The degree is designed to launch a credentialed UK career, not simply add a CV line, so employer engagement runs across every year.

Key Features

Curriculum aligned with BCS, Institute of Analytics and Alan Turing Institute engagement material.
Modules on classical machine learning, deep learning, control and robotics fundamentals.
Structured year-two industry placement supported by LSCE careers service.
Coverage of UK AI Safety Institute themes and responsible-AI practice.
Weekly labs across every study mode with named-tutor visibility.
Final-year capstone on a real intelligent-systems brief.
Regular data-ethics review clinics led by the programme team.
Access to LSCE alumni network across UK AI, data and analytics employers for mentoring and job introductions.
Structured writing workshops covering research notes, model cards and executive briefings.
Regular data-jam and Kaggle-style challenges organised by the LSCE student society.
Weekly clinics with a named programme tutor for one-to-one model review and research coaching.
Access to LSCE's cross-departmental technology library and machine-learning journal subscriptions.
Cohort-wide showcase events at the close of each teaching block with employer observers invited.

What You Will Learn

Model an intelligent product across sensor, actuator, control and learning layers.
Apply classical ML and deep learning to real-world data.
Design controllers for physical and simulated environments.
Handle data pipelines, feature stores and simple MLOps flows.
Evaluate model performance and safety on realistic scenarios.
Use simulation for training and testing intelligent behaviours.
Frame ethical, legal and safety considerations into design.
Present technical work to non-technical audiences.
Read and reproduce a technical paper end to end.
Structure a personal AI portfolio and public repositories suitable for UK job applications.
Manage model reproducibility and lineage for real projects.
Frame ethical, legal and safety considerations from the earliest project stages.
Design experiments that produce statistically defensible findings.
Communicate AI decisions and limitations honestly to non-technical stakeholders.
Manage annotation, curation and consent for real training data.
Balance model performance, cost and safety trade-offs for a real deployment.

Who This Course Is For

School leavers targeting an AI, robotics or systems career.
BTEC and Foundation Year students articulating into an honours degree.
Serving software engineers moving into intelligent-systems work.
International applicants seeking a UK-recognised BSc.
Working professionals topping up an existing HND or Foundation Degree.
International applicants targeting a UK-recognised BEng or BSc with structured UK placement support.
Applicants combining paid work with structured part-time study.
Applicants combining sponsored employer support with rolling intakes.

Career Pathways

Junior AI Engineer
Machine Learning Engineer
Robotics Engineer
Applied AI Researcher
Computer Vision Engineer
IoT Solutions Engineer
Data Scientist

The LSCE careers service maintains contacts with London-region AI startups, robotics firms and research groups, and runs placement support in year two. LSCE undergraduates benefit from placement coaching in year one and structured graduate-scheme support in the final year.

Alumni support continues after graduation, including graduate-scheme job-alert access, mentoring introductions and continued application coaching.

Entry Requirements

A-levels totalling at least 96 UCAS points (or international equivalent), including one science, maths or computing subject.
GCSE English at grade 4/C and Mathematics at grade 4/C (or equivalent).
Applicants with a Level 3 BTEC or a completed LSCE Certificate/Diploma progress on articulation into the BSc in Intelligent Systems Engineering.
IELTS 6.0 overall (no band below 5.5) for non-native English speakers.
Two references, normally one academic and one personal.

International applicants receive dedicated visa, accommodation and English-language guidance alongside the academic decision, so the enrolment step is well supported.

Why Study at LSCE

LSCE, part of Harold International College of London, teaches computing and engineering in small tutor-visible cohorts and partners with UK professional bodies including BCS, the Institute of Analytics and the IET. The London campus places the Alan Turing Institute, AI Safety Institute and London-region robotics teams within easy reach.

Undergraduates choose from on-campus, online with GPU lab provisioning, or distance learning with the same provisioning, and every route benefits from the LSCE careers service and the wider Harold International College catalogue. LSCE students routinely attend London-region professional-body events during their studies, and the campus places central London industry venues within a short tube ride.

LSCE partnerships with UK professional bodies mean the qualifications carry weight with employers. Curriculum alignment is refreshed each year against the latest professional-body guidance and UK sector expectations.

Apply for BSc in Intelligent Systems Engineering

Begin your honours degree with LSCE. Click Enrol Now, admissions will respond within one working day with UCAS guidance, placement information and scholarship review. Rolling intake dates mean early applications receive the widest choice of module electives, mentors and supporting information.

Whether you are moving to London for study or joining an intake from another country entirely, LSCE admissions will walk you through visa considerations, accommodation options and any credit-transfer discussion in the same first response. Prospective students who prefer a phone conversation before applying can request a call-back within one working day.