Becoming a BayeZian II
Master Advanced Stan Programming
Go beyond foundations into production-ready Bayesian modeling: mixture models, survival analysis, Gaussian Processes, physics-constrained likelihoods, and performance engineering—all in Stan with a Columbia professor guiding every step.
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Scott Spencer
Columbia Professor • Stan Collaborator
Build on Strong Foundations
This advanced course assumes mastery of foundational Bayesian concepts and R/Tidyverse fluency.
BayeZian I
Priors, likelihoods, posteriors, GLMs, hierarchical models, cmdstanr basics.
View Course →Production-Ready Advanced Bayesian Skills
Move beyond textbook examples to models that handle real-world complexity: overdispersion, censoring, irregular time series, and mechanistic constraints.
Mixture & Zero-Inflated Models
Handle overdispersion and excess zeros with NB, ZIP, ZINB, and hurdle models.
Rating & Ranking
Plackett-Luce, ordinal regression, and pairwise comparisons in Stan.
Survival Analysis
Weibull and discrete-time hazard models for time-to-event data.
AR & Time Series
Autoregressive processes with regular and irregular time gaps.
Splines & Tensor Products
B-splines, 2D tensor products, and Kronecker tricks for flexible fits.
Gaussian Processes
Full GP priors with Cholesky decomposition and hyperparameter tuning.
HSGP Approximations
Hilbert-space approximate GPs for scalable nonparametric modeling.
Physics-Constrained
Embed mechanics into likelihoods: sailing, golf putting, base running.
19 Advanced Modules
From workflow mastery through mixture models, survival analysis, Gaussian Processes, and computational performance optimization.
Scott Spencer
Scott Spencer is one of the world's foremost experts in applied Bayesian analysis. As a Columbia professor and Stan collaborator, his methods power decisions at Amazon, Johnson & Johnson, Vevo, and leading sports franchises. In this advanced course, Scott shares the production-ready patterns and performance optimizations that distinguish academic exercises from real-world Bayesian systems.
Trusted by Analytics Leaders
"Scott Spencer brings Bayesian modeling alive. He not only explains the math, but shows how to implement models in Stan that are clear, scalable, and ready for research or production."
"AthlyticZ has completely transformed the learning approach to data science through the use of sports-based problems. The instructors are the best of the best."
Designed for Flexibility & Impact
Mix clear instruction, continuous assessment, and applied projects—learn at your pace and show real results.
Prerecorded Video Lessons
Learn on your schedule with concise, high-quality videos you can pause, replay, and revisit.
Assignments & Exercises
Reinforce concepts with practical exercises that build intuition in real workflows.
Continuous Assessment
Low-friction quizzes give you immediate feedback and keep you on track.
Hands-On Projects
Tackle real analytics problems with portfolio-ready case studies.
Supplementary Resources
Curated readings, Stan files, and R scripts to deepen understanding.
Interactive Features
Lesson-embedded notes and preloaded code for hands-on learning.
Join the Elite Analysts Who
Ship Production Bayesian Models
Advanced Bayesian skills separate you from the crowd. Master the techniques that power decisions at top tech companies, pharmaceutical giants, and elite sports organizations.