Bayesian Statistics Courses and Certifications

Bayesian Statistics: From Concept to Data Analysis

10 ratings

Learn Bayesian statistics from probability and Bayes' theorem to conjugate models for Bernoulli, Poisson, and normal data, plus Bayesian linear regression, using R or Excel.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Bayesian Statistics

12 ratings

Apply Bayes' rule to turn priors into posteriors: work with conjugate families, credible intervals, Bayes factors, and Bayesian regression with model averaging in R.

• Coursera
• 7 weeks, 5 hours a week
• Self-Paced
• Paid Course

Career Certificate

Bayesian Statistics

3523 ratings at Coursera

Learn Bayesian methods in R — conjugate models, MCMC, mixture models, and dynamic linear models — to analyze data, forecast time series, and build statistical models.

• Coursera
• 8 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 5 courses

Bayesian Statistics: Techniques and Models

497 ratings at Coursera

Build, fit, and compare Bayesian models in R and JAGS: MCMC with Metropolis-Hastings and Gibbs sampling, linear regression, ANOVA, logistic and Poisson regression.

• Coursera
• 5 weeks, 6 hours a week
• Self-Paced
• Paid Course

Introduction to Bayesian Statistics for Data Science

Learn Bayesian statistical inference, computing posterior distributions with conjugate families, improper and objective priors, Monte Carlo simulation, and Bayesian linear regression in R.

• Coursera
• 5 weeks, 7 hours a week
• Self-Paced
• Paid Course

Bayesian Statistics: Mixture Models

63 ratings at Coursera

Learn mixture models: derive their likelihood function, fit them by maximum likelihood and Bayesian estimation, and apply them to data in R.

• Coursera
• 5 weeks, 4 hours a week
• Self-Paced
• Paid Course

EDUCBA

Bayesian Statistics: Excel to Python A/B Testing

27 ratings at Coursera

Apply Bayesian inference to A/B testing and healthcare analytics: run MCMC sampling with PyMC, fit hierarchical models, and build Bayesian probability tables in Excel.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

Bayesian Statistics: Capstone Project

10 ratings at Coursera

Perform conjugate Bayesian analysis of autoregressive time series, apply order and component selection criteria, fit location mixtures of AR(p) models, and report a full analysis.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Bayesian Computational Statistics

Learn Bayesian inference from prior and posterior distributions to hierarchical models, MCMC and simulation methods, and Bayesian regression, implemented in R or Python.

• Coursera
• 9 weeks, 10 hours a week
• Self-Paced
• Paid Course

Bayesian statistics

6 ratings at OpenLearn

This free course is an introduction to Bayesian statistics. Section 1 discusses several ways of estimating probabilities. Section 2 reviews ideas of conditional probabilities and introduces Bayes’ ...

• OpenLearn
• 12 hours
• Self-Paced
• Free Certificate

Introduction to Bayesian Statistics Using R

10 ratings at edX

Learn the fundamentals of Bayesian approach to data analysis, and practice answering real life questions using R.

• edX
• 6 weeks, 5-10 hours a week
• Self-Paced
• Free Online Course (Audit)

Advanced Bayesian Statistics Using R

6 ratings at edX

Now that you know the basics of Bayesian inference, dive deeper to explore its richness and flexibility more fully. Let’s take a closer look at modeling latent variables, Bayesian model averaging, gen

• edX
• 6 weeks, 5-10 hours a week
• Self-Paced
• Free Online Course (Audit)

Career Certificate

Bayesian Statistics Using R

This program provides a practical introduction to applied Bayesian data analysis, combining theory, philosophy and computational facility with the emphasis on formulating and answering real life quest

• edX
• 12 weeks, 5-10 hours a week
• Self-Paced
• $338.00
• 2 courses

Bayesian Data Analysis in Python

266 ratings at DataCamp

Bayesian data analysis is an increasingly popular method of statistical inference, used to determine conditional probability without having to rely on fixed constants such as confidence levels or p-values.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Richard McElreath

Bayesian Statistics Without Frequentist Language

An insider’s perspective on Bayesian statistics, exploring priors, joint models, and generalized linear mixed models without relying on frequentist language.

• YouTube
• 51 minutes
• Self-Paced
• Free Video