Live Cohort 4 Weeks Beginner - Intermediate

Applied Bayesian Modeling Workshop

— Interactive, Real-World Bayesian Modeling with PyMC Experts

Join our expert-led, 4-week cohort to build a deep, practical understanding of Bayesian modeling with PyMC. Learn through live sessions, hands-on projects, and personalized guidance — starting June 2.

What you'll learn

  • How to build and interpret Bayesian models to solve real-world problems.
  • How to run and diagnose MCMC workflows for reliable, interpretable results.
  • Practical skills in using PyMC to model uncertainty and understand complex systems.
  • Debugging, improving, and scaling models that apply to your own work.

About this course

This hands-on, expert-led workshop from the developers of PyMC will take you from foundational Bayesian thinking to advanced modeling techniques. Designed for engineers, analysts, and scientists, this course emphasizes practical use over academic formality, helping you unlock the power of Bayesian methods in your work. At the end of this course, you'll understand how Bayesian models work and how to confidently apply them to your own data and challenges. Topics include:

  • Bayesian Thinking & Model Building
  • Hands-On MCMC & Inference Techniques
  • Advanced Topics: Hierarchical, Causal, & Time Series Models

The workshop is delivered through 2-hour live sessions twice a week over four weeks. All sessions are recorded and available for the duration of the workshop. Students will have access to a private GitHub repository with all code examples and a dedicated Discord server for communication with instructors and fellow learners.

Who should join?

This course is ideal for software engineers, data analysts, and data scientists who want to move beyond black-box models and start building interpretable, flexible Bayesian models. No prior Bayesian experience is required, just curiosity and some Python.

Course Outline

Date Time (ET) Instructor Topic
June 2 11am - 1 pm
Chris Fonnesbeck Chris Fonnesbeck
Intro to Bayesian modeling and PyMC
June 4 11am - 1 pm
Allen Downey Allen Downey
Building Models in PyMC
June 9 11am - 1 pm
Vianey Leos Barajas Vianey Leos Barajas
MCMC
June 11 11am - 1 pm
Vianey Leos Barajas Vianey Leos Barajas
Priors and Likelihood Choices
June 16 11am - 1 pm
Vianey Leos Barajas Vianey Leos Barajas
Bayesian Regression
June 18 11am - 1 pm
Allen Downey Allen Downey
Hierarchical Models
June 23 11am - 1 pm
Chris Fonnesbeck Chris Fonnesbeck
Causal Inference Models
June 25 11am - 1 pm
Allen Downey Allen Downey
Time Series Models

Earn a certificate of completion

Certificate of Completion
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Instructors

Chris Fonnesbeck
Chris Fonnesbeck
Chris is a Principal Quantitative Analyst at PyMC Labs and an Adjoint Associate Professor at the Vanderbilt University Medical Center, with 20 years of experience as a data scientist in academia, industry, and government. He is interested in computational statistics, machine learning, Bayesian methods, and applied decision analysis. He hails from Vancouver, Canada and received his Ph.D. from the University of Georgia.
Allen Downey
Allen Downey
Allen Downey is a Principal Data Scientist at PyMC Labs and professor emeritus at Olin College. He is the author of several books about programming and data science, including Think Python, Think Bayes, and Probably Overthinking It.
Vianey Leos Barajas
Vianey Leos Barajas
Vianey Leos Barajas is an Assistant Professor, jointly appointed between the Department of Statistical Sciences and School of the Environment at the University of Toronto. She works in the areas of ecological statistics, time series modeling, and Bayesian statistics.

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What students are saying

We regularly teach this workshop in various companies and got great feedback along the way

Still Having Doubts?

No prior experience with Bayesian methods is required. Familiarity with Python and basic statistics is helpful.
There are 16 hours of live instruction: two 2-hour live sessions each week over four weeks, for eight sessions total. You'll have notebooks and access to instructors via Discord between sessions.
Yes, sessions will be recorded and available to participants for the duration of the course.
Yes, a shared private repository will have all the code used in class.
No worries! Recordings are available for the duration of the workshop and you'll still have access to instructors via Discord for help.

If the Participant cancels the subscription, a refund of the Fee will only be provided if the cancellation is made at least 7 days prior to the start of the Workshop.

Additionally, the Participant, as a natural person, has the right to withdraw from the subscription within 14 days of registration and receive a full refund, provided that the Workshop has not yet been delivered. See our full Terms and Conditions .

Applied Bayesian Modeling Workshop

  • Beginner - Intermediate
  • Starts June 2
  • 4 Weeks
  • 8 Live Workshops
  • Access to Alumni Discord Q&As
  • Instructors: Chris Fonnesbeck, Vianey Leos Barajas, Allen Downey
Early Bird: $1,499 $1,699
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Looking for a team offer?

Contact us at info@pymc-labs.com to get a special group rate for multiple registrations from the same company.