Learn how to enhance your modelling abilities and better communicate risk

Building easy to interpret models isn’t a nice to have anymore it is the reason people pay for models in the first place

Level up your Analytical/Data Science skills

Check out this free screencast below.

My complete, self-study probabilistic programming course is trusted by members of top machine learning schools, companies, and organizations, including Harvard, Quantopian, Farfetch, Mailchimp, Uber, Google, University of Chicago and more!

Build robust models and interpret them

Bayesian Analysis provides robust ways of interpreting parameters. Such as which rugby team is the best at attacking!

Learn how to understand if your model is good

Trusting your model is super important. Probabilistic Programming has robust methods for evaluating models. I'll show you how.

Overview

Enhance your Data Science skills with Probabilistic Programming

Incorporate domain knowledge, handle small but complex data and enhance your interpretability of your models.

Bayesian models are used in a range of verticals such as Pharmaceuticals, Travel, Insurance, Supply Chain and Finance.

This course provides over 4 hours of exclusive content.

Building interpretable models isn’t nice to have anymore it’s the reason people pay for models in the first place.


You are paid as an analyst or Data Scientist or Engineer to support decision making. 

In other words, you get paid to:

  1. Build models that get adopted by an organisation or customers
  2. Provide highly insightful (and influential) advice on a business strategy or process

This is impossible without trust. In fact according to recent research on consumer attitudes to AI - one of the top concerns is trusting models.

If you don’t get buy-in or trust for your models, you're leaving money on the table.


Step-by-step Instructions for Building more Interpretable models and opening up new product building opportunities

 
Our mission is to give data scientists and engineers the training and tools that they need to stop worrying about things like not getting buy in, how to incorporate domain knowledge into models, and how to deal with complex small data problems.

As an Probabilistic Programming Primer student, you will receive:

  • Introductions to Bayesian Statistics, PyMC3, Theano and MCMC
  • Descriptive Overviews of Core Models and the Value of Probabilistic Programming
  • Walkthrough Videos That Show You Exactly How to Build and Debug these models
  • Documents and Notebooks Designed to Help you upskill and understand the technical underpinnings and how Probabilistic Programming relates to Deep Learning. These are based on hours of lectures and workshops internally at top startups and at major Data Science conferences.
  • Guidance and Support From a Large (and Growing!) Community of Like-minded Data Scientists
  • Lifetime Access to Our Private Slack Community of Over 150 Ambitious Data Scientists and some core contributors of PyMC3 ($130/year value) 
  • Over 20 screencasts - Screencasts taking you through both the theory and the implementation of Probabilistic Programming. 

Ready to level up your data science skills?

Let's get started!



Register Today

What the pros and students are saying

Peadar has been producing insightful educational material on Data Science and Bayesian Stats for years. Increasingly these Bayesian methods will become important, particularly in regulated sectors.
Alejandro Correra Bahnsen - VP Research
Peadar has a great deal of experience working with probabilistic programming and communicates the fundamentals of Bayesian methods extremely well. He is in an excellent position to guide people through a course like this.
Eoin Hurrell - Data Scientist
I was so impressed with the clarity of Peadars' vision and writing that I included references from him in an open access online course, Sport Informatics and Analytics.
Professor Keith Lyons
Unlike academia or blogs which focus solely on theory or application,  Peadar combines both in those course to set a solid foundation for his students. With the knowledge from this course students will be empowered in Bayesian methods, whether they want to read papers, or start applying the methods in PyMC3 themselves
Ravin Kumar - Engineer and Course student
Peadar has turned his practical experience with Bayesian methods into a course that explains the nuts and bolts of Bayesian statistics and probabilistic programming at a good pace.#PyMC3 #ArviZ
Osvaldo Martin - PyMC3 and ArviZ contributor
The probabilistic programming primer is an incredible course that offers a fast track to an incredibly exciting field. Peadar clearly communicates the content and combines this with practical examples which makes it very accessible for his students to get started with probabilistic programming. 
Peter Verheijen - Entrepreneur and Course Student
I'm currently doing your probabilistic programming primer, after recently completing a data science immersive course - and I think it's brilliant. Very easy to understand, thanks!
Justin Crowe - Data Scientist

Probabilistic Programming Primer

Probabilistic Programming is one of those tricky areas of Machine Learning In this course join Peadar Coyle a core-developer of PyMC3 as helps you learn...

View course £200

30 minute coaching session

Break through your data strategy or modelling challenges with a 30 minute coaching session.

View course £100

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