Bayes camp

Tailored training and coaching
Experienced trainers
Impartial advice

Photo of teaching in progress


Training

We provide tailored on-site courses for teams working with data, and affordable workshops open to all. Our specialities are: introducing data science, stats, machine learning and AI for managers; Bayesian modelling and software; data visualisation; statistics for health research and clinical audit. Browse through the topics and future ticketed workshops, or email robert@bayescamp.com to discuss your team's goals.


Coaching

Take time out from work pressures and look at the big picture of your career working with data. We provide one-to-one, confidential sessions with a trained co-active coach who can ask the right questions, so you can define your values, priorities and goals. email robert@bayescamp.com to discuss your personal journey.


Camp

An immersive three-day BayesCamp in the country (with modern comforts), building expertise in Bayesian analysis away from distractions, with inspiring experienced guest speakers and your fellow future experts. Understand and solve each problem as it comes, rather than picking old tools out of the box. Build effective models and know when and why they will work. Stand out as a confident, thoughtful data analyst. email robert@bayescamp.com to find out more.




Trainers


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Rasmus Bååth

Rasmus (@rabaath) is a Data Scientist who has worked both in academia (Lund University) and industry (castle.io, King, DataCamp). He has a PhD in cognitive science. Currently he's working on using data and Bayes for cybersecurity at Castle.io. He's passionate about Bayesian statistics, good graphs and free coffee, and blogs at Publishable Stuff.


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Robert Grant

Robert (@robertstats) started BayesCamp after teaching and data analysis in health and social care statistics (St George's University of London, Kingston University, National Clinical Guidelines Centre, National Institute for Health & Care Excellence, Royal College of Physicians). He's a medical statistician who went on to learn machine learning techniques and see how data science actually happens in commercial settings. He has trained and consulted for many organisations in the public and private sectors. Robert loves Bayesian analysis and data visualisation: he wrote the ASA / CRC Press book "Data Visualization: charts maps and interactive graphics" in 2018, and is one of the Stan developers.


Photo of Leto Peel

Leto Peel

Leto (@PiratePeel) has over 10 years of experience in theoretical and applied machine learning research in both academia and industry. His research interest is in analysis of complex networks. He has worked on many research projects in biology, computer vision, crime science, economics, game theory, geography, geomatics, physics and security. His collaborations in industry include Airbus, BAE Systems and London Metropolitan Police, and in academia include Imperial College London, MIT, Santa Fe Institute and Oxford University.



Software


Stan

The world-leading Bayesian software comes with interfaces for R, Python, Julia and more. It is tried and trusted for almost every kind of model you might want to fit to your data. It is used by every serious data science organisation you can name. But maybe you find it a little scary, a little unapproachable. Let's break through that barrier with an introductory or specialist course.


R

There are many ways to access powerful Bayesian tools in R, from user-friendly, high-level packages like brms and rethinking through to the NUTS and bolts of Stan, JAGS and BUGS. An overview course will show you the options and let you weigh up which one works best for you and your data.


BUGS / JAGS

Bayesian inference Using the Gibbs Sampler is still the world's favourite Bayesian software, and Just Another Gibbs Sampler is close behind. An introductory course will get you up and running with these tools and show you many of the models that have been effectively programmed in them already.



Company principles

  • We focus on a few areas of specialist strength, we don't trick clients with hype.
  • We contribute to local tech and science communities, and prioritise face-to-face, local work.
  • Our work must promote healthy, happy, sustainable workplaces and professional practices for people working with data, whether they call it statistics, data science, machine learning or artificial intelligence. We help people to confront and change stressful, unrealistic, uninformed expectations.
  • We will work with any individuals or organisations based anywhere in the world (unless prevented by UK law, and except any foreign government); dialogue builds a better world. No BayesCamp activity ever physically takes place in jurisdictions that endorse torture or extrajudicial killings, or that legislate discrimination.
  • bayescamp.com does not contain tracking or snooping code of any form.
  • We never use exploitative subcontracting practices for individuals, such as zero-hour contracts. If we're happy to have someone supply BayesCamp training or coaching, we support them with employment and the legal protection that brings them.
  • Prizes and awards for lifetime achievement are inimical to nurturing new ideas, collaboration, and early-career diversity. BayesCamp and its directors never accept any such prize, and give awards rewarding projects, not individuals.

Research

BayesCamp supports and conducts research in Bayesian methodology. Read more about our work here.

BayesCamp Ltd is incorporated in England and Wales, number 10666858. The term 'BayesCamp' and the Gaussian tent logo are registered trademarks.