24/06/2026
We’re delighted to share that Cambridge Spark has been recognised at The Quality Professionals Awards 2026.
We were named Winner – Quality Improvement Initiative of the Year for our AI-Powered Quality Improvement initiative, and were also finalists for Compliance Team of the Year and Quality Team of the Year.
To top off an incredible afternoon, we also received the final award of the night: Outstanding Contribution to Quality Improvement, selected by the judges.
As the judges shared, our approach to QA frameworks is “freeing up staff from time-consuming administration so they can focus on high-quality teaching and assessment” through work that is “inclusive, scalable and sustainable.”
A huge congratulations to our Quality and Compliance teams, and to everyone across Cambridge Spark who helps drive quality every day.
22/06/2026
AI ambition is everywhere. But turning it into real-world impact takes the right engineering skills.
Join our upcoming webinar, Engineering AI Readiness: Building the Data and AI Skills Your Organisation Needs, to explore how Data Engineers and AI Engineers help organisations move from experimentation to implementation.
📅 09 July 2026
🕛 12 pm BST
We’ll cover why strong data foundations and production-ready AI capability are critical for AI readiness, and how employers can build these skills from within through apprenticeship pathways.
Register now to learn more: https://eu1.hubs.ly/H0wl5vl0
19/06/2026
We’re looking forward to celebrating the achievements of Cambridge Spark apprenticeship alumni at our Celebration of Achievement event on 26 June at London Guildhall.
The event is aimed at recognising and celebrating alumni who completed their apprenticeship programmes over the past year, marking their hard work, growth and success.
Congratulations to all of our apprenticeship finishers. We’re proud to celebrate this important milestone with you.
18/06/2026
When should you use prompting, and when do you need data science?
That was the focus of our latest webinar with Jeremy at Cambridge Spark.
As LLMs and agentic AI become more accessible, the real challenge is knowing which tools are best suited to which types of problems. For fuzzy, fast-moving tasks, LLMs can be incredibly powerful. But where organisations need repeatability, validation and stronger control, data science and machine learning still matter.