Empower every student — from kindergarten to grade 12 — with foundational computational thinking, coding fluency, and real-world AI skills through hands-on, project-based learning.
Our Computer Science & AI pathway guides students through a carefully sequenced journey — starting with visual block coding and tangible robotics in early grades, advancing through text-based programming and data structures, and culminating in machine learning, computer vision, and autonomous systems for high schoolers.
Every lesson is standards-aligned (CSTA, ISTE, Next Gen Science) and comes with teacher guides, assessment rubrics, and differentiated materials so no learner is left behind.
Decomposition, pattern recognition, abstraction, algorithmic design
Block coding → MicroPython → Python, real hardware output
Sensors, actuators, autonomous control, line-following & obstacle avoidance
Machine learning, computer vision, AI ethics, model training & inference
Each track builds directly on the previous, creating a coherent K–12 learning journey no matter where students start.
Ages 5–8 · Foundational
Ages 8–11 · Intermediate
Ages 11–14 · Advanced
Ages 14–18 · Expert
Each pillar is woven throughout the K–12 pathway, deepening in complexity as students advance.
Students learn to break down complex problems into manageable steps, spot patterns, and build generalised solutions — skills that transfer far beyond computer science into every discipline.
A progressive coding journey from drag-and-drop blocks through MicroPython to full Python, with students writing real code that controls physical hardware from day one.
Hands-on kits — smart cars, robotic dogs, mechanical arms — give students immediate, tangible feedback. They build, program, break, and fix, developing engineering resilience alongside technical skills.
From understanding how an algorithm learns from data to training image classifiers and deploying models on edge devices, students experience AI as creators — not just consumers.
Smart sensor networks, data logging, wireless communication, and dashboards teach students how the physical and digital worlds connect — the backbone of the modern economy.
Technical skill alone isn't enough. Students explore bias in AI systems, data privacy, accessibility, and the responsibilities of building technology that affects real communities.
Everything is designed so a teacher with no CS background can deliver a world-class lesson on day one.
Every lesson maps to CSTA K–12 CS Standards, ISTE Student Standards, and Next Generation Science Standards — making scheduling and reporting effortless.
Students don't just read about concepts — they build working artefacts. Each unit culminates in a project that solves a real-world problem or answers a genuine question.
Extension challenges, scaffolded support materials, and multiple means of representation ensure gifted learners are stretched while no student is left behind.
Slide decks, video walk-throughs, formative assessment tools, and live professional development so your team feels confident from the very first lesson.
All materials include a standards alignment document so administrators can map every lesson to district requirements in minutes.
Curated hardware that puts real technology in students' hands — paired with curriculum that makes every build meaningful.
A versatile Micro:bit smart car with ultrasonic sensors, line-tracking, RGB LEDs, and IR remote — the perfect introduction to physical computing and autonomous behavior.
An advanced mechanical building kit with PlanetX sensors and AI modules — students design, build, and program complex machines driven by real AI inference.
A four-legged robot powered by Raspberry Pi with built-in camera, voice recognition, and face detection — the ultimate platform for high-school AI and autonomous robotics projects.
Students program Micro:bit to monitor soil, light, and humidity — then automate irrigation decisions. Real IoT, real data, real impact on a problem the world cares about.
A complete IoT learning system — students collect environmental data, transmit it wirelessly, visualise it on dashboards, and build automated responses using conditional logic.
A plug-and-play computer vision module that recognises faces, objects, and colours. Students integrate it with Micro:bit projects to build AI-powered security systems, sorters, and more.
Request a free demo kit, speak with a curriculum specialist, or download our full K–12 scope & sequence — no commitment required.