Call for Speakers

ongoing

Data Science London Meetup

planned future dates

23 Jun 2026, 14 Jul 2026, 11 Aug 2026, 15 Sep 2026, 3 Nov 2026

location

10 Old Bailey, London EC4M 7NG · London London, United Kingdom


Data Science London is a community for people who work with data and AI and want to go deeper.

We're data scientists, AI/ML engineers, and data hackers who meet to share what we're working on; real projects, useful tools, and the techniques actually moving things forward in AI, ML, and data science. The emphasis is always hands-on: deep-dives, demos, and practical knowledge you can take back to your own work.

We've been at this since 2011, we've run a lot of hackathons along the way, and we've grown into one of the largest data science communities in Europe. Throughout, one principle has stayed the same, knowledge should be shared freely and openly.

Whether you're presenting, asking questions, or just listening, you'll be among people who care about the craft and are generous with what they know.

If you're directly involved in ML, AI, or data science work, this is your community. Come learn something, and bring something to share.

open, 4 months left
Call for Speakers
Call opens at 12:00 AM

21 May 2026

Call closes at 11:59 PM

20 Sep 2026

Call closes in GMT Daylight Time (UTC+01:00) timezone.
Closing time in your timezone () is .

Call for Speakers: Data Science London

We're looking for speakers to share what they're working on with one of the largest data science communities.

The format

All talks are in person, 30–40 minutes (English), followed by food, questions, and the kind of conversation that's usually better than the talk itself. We keep it hands-on, our community comes to learn from people doing the actual work, so practical beats theoretical every time.

Topics we're especially interested in

Including, but not limited to:

- Taking AI from PoC to production

- AI adoption: what actually drives it, and what gets in the way

- Real-world use cases of AI, ML, and data science

- Lessons learned (the projects that didn't go to plan are often the best talks)

- AI evaluation: how you know it's actually working

- AI security

- New tools worth knowing about


If you've learned something the hard way and others would benefit from hearing it, we want to hear from you.

What makes a great talk

Real experience over theory. Honest accounts, including what didn't work. Practical takeaways people can apply to their own projects. First-time speakers are very welcome, we're happy to help you shape your session.

How to submit

Send us your proposal via Sessionize, including a clear title, what attendees will learn, and a sentence or two about your experience with the topic. If you're not sure your idea fits, submit it anyway,  we'd rather see a rough idea than miss a good one.

We're looking forward to hearing what you've been building.


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