During our recent open evening at Sutton High School, the Computer Science department unveiled their new cross-Trust Quantum Machine Learning Extension course with a showcase presentation. The event included a keynote address from distinguished guest Dr. Christian Kraglund Andersen, QuTech Academy Lead.
This course, the first of its kind within the Girls’ Day School Trust (GDST), was offered as an extension module for the GDST Space Technology Diploma. Focused on Quantum Machine Learning (QML), the course content was trialed earlier this year at the UKSEDS Student Space Conference and Staffordshire University London. It provided a comprehensive introduction to quantum computing and QML AI in the context of enhanced rocket trajectory prediction. Students explored quantum math matrix multiplication, applied quantum operators foundational to quantum computing, and translated these into Python programming for machine learning AI algorithms. The course concluded with translating a test segment of the AI model onto a Python Qiskit quantum simulator.
This course came at an opportune time, as the department collaborated with developers of Python RocketPy, a rocket simulator for 3D trajectory. Students had the privilege of investigating RocketPy’s use as a mass synthetic data generator for a larger QML project, potentially enhanced with satellite data points for weather and Earth topography, affecting model rocket launches year-round.
Our guest speaker, Dr. Andersen, offered insights on the growing quantum workforce and careers that encompass QML, while leading course students Farah R from Sutton High School and Inayat B from Sheffield High School delivered an inspiring showcase of their coursework ahead of the cross-Trust virtual certificate ceremony that evening.
