Bayesian Statistics Courses and Certifications

Richard McElreath

Statistical Rethinking 2022 - Geocentric Models

Explore Bayesian linear regression, covering model language, generative and statistical approaches, validation, and posterior predictions for a comprehensive understanding of statistical modeling.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Steve Brunton

Conjugate Priors Example - Normal Distribution and the Exponential Family of Distributions

1 review

Explore conjugate priors through Normal distributions and the Exponential Family, demonstrating how Normal likelihoods pair with Normal priors for Bayesian inference.

• YouTube
• 19 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

A Brief Introduction to Nested Sampling - IPAM at UCLA

Explore Nested Sampling for Bayesian model uncertainty and selection. Learn its principles, advantages, and recent extensions like Dynamic Nested Sampling for estimating marginal likelihoods and posterior distributions.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2023 - Missing Data

Explore missing data in DAGs and learn Bayesian imputation techniques for handling incomplete datasets in statistical analysis, with practical examples and insights.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2023 - Multilevel Adventures

Explore multilevel modeling techniques for analyzing clustered data, focusing on varying confounds, district-level effects, and urban-rural differences in Bangladesh fertility studies.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2023 - Categories & Curves

Explore statistical concepts like categories, posterior contrasts, and curves in this comprehensive lecture. Learn advanced techniques for data analysis and modeling using Bayesian methods.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Video

MITCBMM

Bayesian Inference in Generative Models

Explore approximate Bayesian inference methods, including sampling-based techniques and variational inference, with hands-on exercises in implementing algorithms and using probabilistic programming languages.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Toronto Machine Learning Series (TMLS)

Building a Measurement System for Personalization - A Bayesian Approach

Explore Bayesian approaches for measuring personalization effectiveness, optimizing customer assignments, and designing MLOps-inspired measurement platforms for complex hierarchical experiments.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2026 - Categories and Causes - Lecture A04

Explore categorical variables and causal inference in Bayesian statistics through practical modeling techniques and real-world applications.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2026 - Multilevel Models - Lecture B01

Dive into multilevel models and hierarchical statistical thinking with advanced Bayesian techniques for complex data structures.

• YouTube
• 1 hour
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2026 - Garden of Forking Data - Lecture A02

Explore Bayesian reasoning through the garden of forking data metaphor to understand how statistical models update beliefs with new evidence.

• YouTube
• 1 hour
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking 2026 - Introduction to Bayesian Workflow - Lecture A01

Discover Bayesian workflow fundamentals through statistical rethinking principles and practical methodology for data analysis and inference.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Steve Brunton

Bayesian Maximum A Posteriori Estimation - Extending Maximum Likelihood Estimation

Discover Bayesian Maximum A Posteriori Estimation, extending MLE with prior information for robust parameter estimation when data is sparse or expensive.

• YouTube
• 13 minutes
• On-Demand
• Free Video

Steve Brunton

Bayesian Updates and Conjugate Priors

Discover how to update Bayesian models with new data using conjugate priors, ensuring posterior distributions remain in the same family as priors for efficient computation.

• YouTube
• 18 minutes
• On-Demand
• Free Video

From Proof of Work to Proof of Theorems - Bayesian Revolution and Computational Complexity

Explore how Bayesian theory revolutionized cognitive science and AI, examining computational complexity, cryptography, and theorem proving in relation to mental processing and belief systems.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video