Where knowledge is built
A coding and AI programme built to international standards. We bring the curriculum, the platform, and the people. You provide a timetable slot and a room.
Founded by a UK-trained technologist with ten years building digital products for the NHS, a UK bank and a public authority.
Start a ConversationWhat We Deliver
Students build and run their own work from the first lesson. Every unit works toward a portfolio piece they can demonstrate, not a multiple-choice score they forget.
Students begin with visual coding to build computational thinking, then move to Python, HTML/CSS and JavaScript through structured projects. Blocks are where they start, not where they stop. By Year 9 (ages 13–14) they are building working applications.
AI starts in Year 4 (age 8), with what it is and how to use it safely and creatively. From Year 7 (age 11) students learn how language models, classifiers and generative tools actually work. They build with AI APIs and learn to evaluate outputs critically — the skill set employers will expect.
Each year group completes capstone projects: a personal website, an automated data tool, a trained classifier. Students leave with a portfolio of real artefacts, not just a certificate.
We recruit, vet, and train specialist instructors who teach on your premises during timetabled periods. They follow our curriculum and reporting standards, integrated with your school calendar.
Curriculum Spine
A progressive sequence from computational thinking to applied AI, built to run as one timetabled period per week. Aligned to ISTE and CSTA standards, and designed to sit alongside British, American and IB curricula.
Visual and block coding, computational thinking, and what AI is — used safely and creatively. Projects include quiz apps and simple simulations.
The move to text-based code, starting with Python fundamentals: variables, functions, data types. Then full-stack web basics (HTML, CSS, JavaScript), version control with Git, and API integration. AI literacy deepens: how models are trained, prompt engineering, building with AI APIs, and evaluating model outputs for bias and accuracy.
Students undertake extended projects: training classifiers on custom datasets, building full-stack applications, and automating real workflows. This phase produces the portfolio artefacts that demonstrate genuine competence to universities and employers.
How the Partnership Works
ILMERE handles the specialised components. Your school provides the access and environment. Neither side duplicates the other's effort.
Getting Started
We start small so both sides can evaluate the fit. A single-term pilot with one year group, then decide together whether to expand.
We discuss your school's priorities, existing computing provision, and where ILMERE fits.
We recommend a year group and deliver a scoped plan: curriculum outline, schedule, and resource requirements.
Our instructor teaches on site for one term. You observe, we report, students build.
At the end of the pilot we share a detailed outcome report. You decide whether and how to continue.
Students, teachers and school staff sign in to the ILMERE learning platform.