AI helped you train your ML model, but can you vouch for it?

🥁 Join us for an engaging Hackathon!
In a world where AI can create a complete machine learning pipeline in just seconds, how can you ensure its reliability?
As part of London Data Week 2026, this half-day hackathon, co-hosted by Probabl and the GLA Data for London Team, invites participants to take on real policy challenges presented by the Greater London Authority. Issues include youth employment, building decarbonization, and enhancing open data discovery. 🌍

The focus is not only on building a model but also on being able to evaluate, explain, and vouch for it—a skill that’s increasingly vital as AI becomes more prevalent in ML development. Participants will be encouraged to utilize the Python library skore in their evaluations. The winning teams will have the unique opportunity to pitch their solutions to the GLA’s data leadership team!

🗓️ Agenda Highlights

• 9:00-9:30: Doors open
  Arrive early to kick off the day in style!
• 9:30-10:00: Welcome
  Welcome speeches and a demo of skore. Participants will form teams of 2-4 and select their policy problems to tackle.
  Options include:
  • Finding work, education, or training opportunities for London’s youth.
  • Strategies for decarbonizing London’s buildings.
  • Enhancing data search capabilities in London.
• 10:00-12:00: Hackathon
  Tackle your chosen problem using provided datasets, with assessments based on model evaluation and explanation—whether the code is hand-written, AI-generated, or a mix of both.
• 12:00-13:00: Presentations & Prizes
  Short presentations from teams followed by awarding prizes for the winning team in each policy category.

🏆 Prizes and Perks

• Winning Teams (1x per policy problem): 100% discount code for Skolar certification plus the chance to pitch to the GLA's data leadership team in the afternoon.
• All Participants: 100% discount code for Skolar Discovery certification—a valuable credential for your CV and LinkedIn.
• Refreshments and lunch provided.
• Network with fellow data science practitioners and the teams from Probabl and GLA!

📍 Location: London City Hall
🔗 Get your tickets here!