Bayesian Statistics is an approach to data analysis that is entirely based on Baye’s theorem. It offers knowledge about parameters in a statistical model and is updated with the information in observed data. It is widely used in different areas including machine learning, data analysis, sports betting, and more. With that, it is also used by bounty hunters for tracking down shipwrecks full of gold. Below you can find the list of Best + Free Bayesian Statistics Courses with Certificates.

#	Course Name	University/Organization	Ratings	Duration
1.	Introduction to Bayesian Statistics	Udemy	★★★★☆ 4.2	1.5 Hours
2.	Bayesian Statistics: From Concept to Data Analysis	University of California	★★★★★ 4.6	11 Hours
3.	A Comprehensive Guide to Bayesian Statistics	Udemy	★★★★☆ 4.3	03 Hours
4.	Bayesian Statistics: Techniques and Models	University of California	★★★★★ 4.8	29 Hour
5.	Bayesian Machine Learning in Python: A/B Testing	Udemy	★★★★★ 4.6	11 Hours
6.	Bayesian Statistics Videos	LinkedIn Learning	—	—
7.	Bayesian Statistics: Mixture Models	University of California	★★★★★ 4.5	21 Hours
8.	Bayesian Statistics: Generalized Linear Models with R	Udemy	★★★★★ 4.8	06 Hours
9.	Bayesian Statistics	Duke University	★★★★☆ 3.8	34 Hours
10.	Advanced Bayesian Statistics Using R	University of Canterbury	—	60 Hours

In order to help our readers in taking a knowledgeable learning decision, TakeThisCourse.net has introduced a metric to measure the effectiveness of an online course. Learn more about how we measure an online course effectiveness.

Best + Free Bayesian Statistics Courses with Certificates

Introduction to Bayesian Statistics

- - Woody Lewenstein via Udemy
  - 6,581+ already enrolled!
  - ★★★★☆ (404 Ratings)

Introduction to Bayesian Statistics

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Good ★★★★☆	Good ★★★★☆	Fair ★★★☆☆	Fair ★★★☆☆

In this beginner-level course, the instructor will give a detailed introduction to Bayesian Statistics.

The reason why we chose this course is its focus on explaining what probability means and how to distinguish the Bayesian approach from the Frequentist approach.
This course is for those who are starting their journey in Bayesian Statistics and need to understand it more deeply.

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This was a great course. The instructor seemed quite capable and offered just the right amount of content in his course. The quizzes were great and really engaging. Solving these quizzes helped me understand everything taught in the course. I recommend this course to those interested in Bayesian Statistics. (Andrew W, ★★★★★)

Bayesian Statistics: From Concept to Data Analysis

- - University of California via Coursera
  - 140,103+ already enrolled!
  - ★★★★★ (3,069 Ratings)

Bayesian Statistics - From Concept to Data Analysis

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Excellent ★★★★★	Excellent ★★★★★	Good ★★★★☆	Good ★★★★☆

In this course, you will get a detailed introduction to the Bayesian approach to statistics. Here the instructor will shed light on the concept of probability and move to the analysis of data.

The reason why we chose this course is its focus on explaining the philosophy of the Bayesian approach in detail. You will also understand how to implement it for common types of data.
This course is for those who wish to understand all about the Bayesian approach and how it allows for better accounting of uncertainty.

This course offers a great introduction to Bayesian Statistics. The instructor covered the basic concepts in an amicable way. The workload is quite balanced and the course offers a reasonable amount of quizzes/exercises. (Georgi S, ★★★★★)

A Comprehensive Guide to Bayesian Statistics

- - Twinkle Sethi via Udemy
  - 420+ already enrolled!
  - ★★★★☆ (102 Ratings)

A Comprehensive Guide to Bayesian Statistics

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Good ★★★★☆	Good ★★★★☆	Fair ★★★☆☆	Fair ★★★☆☆

In this course, you will get a detailed overview of Statistical Inference. Here the instructor will talk about both Frequentist and Bayesian approaches to Statistical Inference in detail.

The best thing about this course is its focus on explaining the Bayes Theorem and all its applications in Bayesian Statistics. You will also learn to build a good intuitive understanding of Bayesian Statistics with real-life illustrations.
This course is for those who wish to master the key concepts of Prior and Posterior distribution and learn to solve exam-style numerical problems of computing Posterior Distribution.

Find out more about where to explore accredited stats courses and boost your statistical knowledge.

A great course where the lecturer clearly knows what she is talking about. I found her to be quite passionate about helping her students. She is the best and even sent me an email to answer my question in detail. Not all the instructors do that and that is why I really appreciate her efforts. Glad to have found her. (Yi W, ★★★★★)

Bayesian Statistics: Techniques and Models

- - University of California via Coursera
  - 52,091+ already enrolled!
  - ★★★★★ (457 Ratings)

Bayesian Statistics - Techniques and Models

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Excellent ★★★★★	Excellent ★★★★★	Good ★★★★☆	Good ★★★★☆

In this engaging course, you will get to expand your Bayesian toolbox by learning different computational techniques. Here the instructor will explain in detail the Markov Chain Monte Carlo (MCMC) method.

The reason why we chose this course is its focus on explaining how to construct, fit, assess, and compare Bayesian Statistical models for answering different scientific questions that involve continuous, binary, and count data.
This course is for those who wish to understand a few basic modeling techniques that are commonly used by statisticians.

Find out how you can bolster your data science expertise by exploring our curated selection of courses in Statistical Data Science.

This course is a perfect continuation of the Bayesian Statistics course offered by Professor Herbert Lee. Not only it is mathematically rigorous but also offers applied content. I can say this course is excellent for those who are new to Bayesian Statistics. I believe this course is a perfect way to start using Bayesian models in practice confidently. (Igor K, ★★★★★)

Bayesian Machine Learning in Python: A/B Testing

- - Lazy Programmer Inc. via Udemy
  - 34,929+ already enrolled!
  - ★★★★★ (6,132 Ratings)

Bayesian Machine Learning in Python - AB Testing

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Excellent ★★★★★	Good ★★★★☆	Fair ★★★☆☆	Fair ★★★☆☆

Are you interested in learning some of the very best data science, machine learning, and data analytics techniques for marketing, digital, media, and online advertising? If yes then this course is for you.

The best thing about this course is its focus on explaining how to use adaptive algorithms for improving A/B testing performance. Here you will also understand the difference between Bayesian and Frequentist statistics.
This course is for those who wish to understand how to apply Bayesian methods to A/B testing.

An excellent course that covers a lot of concepts, technical details, and even hands-on coding. This course strikes a perfect balance to facilitate my learning. I am very much satisfied with the content of this course. (Zach H, ★★★★★)

continue with more Bayesian Statistics Courses with Certificates…

Bayesian Statistics Videos

- - via LinkedIn Learning

To help learners understand what Bayesian Statistics is and how this approach is used in data analysis, LinkedIn Learning offers different Bayesian Statistics Videos that contain the best learning material. Whether you want to understand what Bayesian Interference is or need an introduction to Bayesian Analysis or even understand the foundations of statistics, LinkedIn Learning has a course for all.

Bayesian Statistics: Mixture Models

- - University of California via Coursera
  - 7,516+ already enrolled!
  - ★★★★★ (41 Ratings)

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Excellent ★★★★★	Excellent ★★★★★	Good ★★★★☆	Fair ★★★☆☆

In this course, the instructor will help you understand the basic concepts of mixture models in detail.

The best thing about this course is its focus on explaining all about the maximum likelihood estimation for mixture models.
This course is for those who wish to understand the applications of mixture models in Bayesian Statistics in detail.

An excellent course that offers excellent learning material, lecture videos, and programming assignments. This course taught me so much about both EM and MCMC. When I started to solve the assignments I thought it would be very difficult but after completing each lecture video, things started to make sense and everything seemed easy. (Rajendra A, ★★★★★)

Bayesian Statistics: Generalized Linear Models with R

- - Andre Marques via Udemy
  - 58+ already enrolled!
  - ★★★★★ (9 Ratings)

Bayesian Statistics - Generalized Linear Models with R

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Excellent ★★★★★	Good ★★★★☆	Fair ★★★☆☆	Fair ★★★☆☆

This course will explain Bayesian Statistical Modeling with R in detail. Here you will also understand all about the estimated linear regression models for binary and binomial data.

The reason why we chose this course is its focus on explaining all about model rates and ratios. You will also learn to use discrete and continuous models in detail.
This course is for those who wish to learn to use the exponential family of distribution in Bayesian Statistics.

The course is fine and offered content that is of great value. Still, there are some questions I was hoping to find answers to but didn’t. (Rafael L, ★★★★☆)

Bayesian Statistics

- - Duke University via Coursera
  - 72,670+ already enrolled!
  - ★★★★☆ (787 Ratings)

Bayesian Statistics

Online Course Effectiveness Score
Content	Engagement	Practice	Career Benefit
Good ★★★★☆	Good ★★★★☆	Fair ★★★☆☆	Fair ★★★☆☆

In this intermediate-level course, the instructor will explain how to use Baye’s rule to transform prior probabilities into posterior probabilities.

The best thing about this course is its focus on explaining how to apply Bayesian methods to several practical problems and show end-to-end Bayesian analysis.
This course is for those who wish to understand all about Bayesian comparisons of means and proportion and how to apply Bayesian methods to several practical problems.

This course has taught me so much about Bayesian Statistics. Yes the content was very difficult I wouldn’t lie but it was presented in such a simple manner that everything became easier to understand. (Younes E, ★★★★☆)

Advanced Bayesian Statistics Using R

- - University of Canterbury via edX
  - 60 Hours of effort required!
  - Study Type: Self-paced

In this engaging class, the instructor will explain how to do multivariate analysis within the context of mixed effects linear regression models. Here you will understand the structure, assumptions, diagnostics, and interpretation of Bayesian Statistics in detail.

The reason why we chose this class is its focus on explaining how Monte Carlo integration works and how it can be implemented in the MCMC Metropolis-Hastings algorithm in R.
This class is for those who wish to understand the advanced concepts of Bayesian Statistics.

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10 Best + Free Bayesian Statistics Courses with Certificates