Artificial intelligence and data science education — resources and lessons learned


Between September 2021 and March 2022, we held a series of research seminars and a panel on AI, machine learning and data science education, in collaboration with The Alan Turing Institute.

This page collates the resources and links shared as part of that seminar series – including resources shared by our seminar speakers and by seminar participants – as well as resources from the Raspberry Pi Foundation. We hope you find it helpful.

Resources from our seminar speakers


AI Ethics and Engagement with Children and Young People (7 Sept 2021)

Exploring the data-driven world: Teaching AI and ML from a data-centric perspective (5 Oct 2021)

ML education for K-12: emerging trajectories (2 Nov 2021)

  • Professor Matti Tedre and Dr Henriikka Vartiainen from the University of Eastern Finland shared their research on teaching machine learning in schools, and what changes to computational thinking are needed. They shared:
    • A classroom tool for creating machine learning apps
    • An academic paper on teaching machine learning in K–12 classrooms and pedagogical and technological trajectories
    • An academic paper about the changes needed to computational thinking (CT 2.0)

What is it about AI that makes it useful for teachers and learners? (7 Dec 2021)

Teaching Artificial Intelligence in K-12 (11 Jan 2022)

Teaching youth to use AI to tackle the Sustainable Development Goals (1 Feb 2022)

  • Tara Chklovski, CEO of Technovation, shared learnings from Technovation’s work inspiring and supporting girls and young women to use technology to tackle complex real-world problems. She shared:
    • Technovation’s curriculum, which includes lesson plans and video tutorials
    • Technovation’s impact reports, which examine how their programmes affect participants
    • App Inventor, the block-based programming environment used by Technovation for their beginner curriculum. App Inventor also offers several AI extensions
    • An example of a presentation used to promote Technovation sessions

Democratizing AI education with and for families (1 Mar 2022)


Resources from the Raspberry Pi Foundation


Teacher professional development resources

Formal education resources

Within the Teach Computing Curriculum, which we’ve created as part of the National Centre for Computing Education (NCCE), we include classroom lesson materials that build data literacy and fundamental data science skills:

On our Isaac Computer Science online learning platform for GCSE and A level Computer Science students (age 14–18), we include content to help learners increase their data literacy and data science skills:

Resources shared by seminar participants


Resources related to AI ethics

Classroom resources for teaching machine learning and AI

Software for teaching young people about machine learning and AI

Classroom resources for teaching data science

Reading and teacher professional development


We are updating this page regularly.