From 14th–16th September, AIchemy and LIV.INNO welcomed researchers to the University of Liverpool for three days of hands-on learning at our Data Intensive Science School. Designed to build practical skills at the intersection of data science, AI and scientific computing, the school brought together researchers, students and experts from across disciplines to explore the tools and approaches increasingly shaping data-intensive research.
With much of the programme dedicated to practical workshops and interactive sessions, participants had the opportunity to get hands-on, try new approaches and develop skills they could take directly back into their own research.
From Data to Scientific Software
Sessions explored Apache Spark and scalable data processing, alongside the collection and preparation of data for machine learning, providing practical experience of working with the large and increasingly complex datasets encountered across scientific research.
The programme also looked at the tools and practices that underpin effective computational research. Workshops on Git and publishing code explored version control, collaborative coding, reproducibility and how researchers can share and maintain scientific software more effectively.
Participants were also introduced to PyAutoFit, exploring probabilistic modelling and automated model fitting, before turning their attention to scientific Python and the important question of how not to make NumPy slow.
Together, the sessions highlighted that effective data-intensive science isn’t only about choosing the right algorithm or model. The way data, code and computational workflows are structured, managed and shared can be just as important.
Exploring What’s Next
Sessions on agentic AI for data analysis and open-source science explored how emerging AI systems and collaborative research ecosystems could influence scientific workflows, productivity and discovery.
Participants then had the opportunity to bring their learning together through real-world challenges, applying ideas and techniques from across the programme to practical scientific and data-driven problems. Alongside the practical workshops, the school created space to look towards some of the wider developments changing the way researchers work.
Three Days of Learning, Coding and Collaboration
With so much of the programme spent working through practical exercises, troubleshooting code and testing new tools, the Data Intensive Science School was as much about participation as presentation.
It also provided an opportunity for researchers from different disciplines and institutions to learn alongside one another, exchange ideas and make new connections, with conversations continuing beyond the workshops during the school’s networking social.
A huge thank you to Dr Edward Bennett, Dr Prakriti Kayastha, Dr Bradley Martin, Dr James Nightingale, Dr Louise Butcher, Dr James Todd, Dr Abdoulatif Cisse, Dr Alex Hill, Dr Andrew Mason, Dr Giulia Ballabio and Dr Pardis Biglarbeigi for sharing their expertise and delivering sessions across the three days.
Thank you also to everyone who joined us in Liverpool and threw themselves into the practical sessions. We hope you left with some new skills, new tools and, importantly, some new ideas to take back into your own research.
And finally, a huge thank you to LIV.INNO for working with AIchemy to make the school possible.
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We look forward to seeing you at our next event!