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Bayesian Statistics: Mixture Models
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Bayesian Statistics: Mixture Models

This course is part of Bayesian Statistics Specialization.

Course Cost

Free course

Intermediate

Skill Level

18 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Bayesian Statistics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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4.5

9,916 Enrolled

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English

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olive-leaves-logo

4.5

9,916 Enrolled

olive-leaves-logo

English

What you'll learn

  • Implement mixture models using maximum likelihood and Bayesian approaches

  • Develop MCMC algorithms for mixture model estimation

  • Apply mixture models to clustering and classification problems

  • Compute mixture distribution properties accurately

  • Implement advanced statistical algorithms in R

  • Evaluate model performance using Bayesian criteria

Skills you'll gain

Bayesian Statistics
Mixture Models
MCMC
R Programming
EM Algorithm
Statistical Learning
Density Estimation
Clustering
Classification
Markov Chain

This course includes:

7.4 Hours PreRecorded video

11 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 5 modules in this course

This comprehensive course covers advanced topics in Bayesian statistics, focusing on mixture models and their applications. Students learn theoretical foundations and practical implementations using R programming. The curriculum includes maximum likelihood estimation, Bayesian estimation, MCMC algorithms, and applications in density estimation, clustering, and classification. Special attention is given to computational considerations and model selection criteria.

Basic concepts on Mixture Models

Module 1 · 4 Hours to complete

Maximum likelihood estimation for Mixture Models

Module 2 · 3 Hours to complete

Bayesian estimation for Mixture Models

Module 3 · 3 Hours to complete

Applications of Mixture Models

Module 4 · 4 Hours to complete

Practical considerations

Module 5 · 4 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Bayesian Statistics Specialization

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Bayesian Statistics: Mixture Models

Intermediate

Skill Level

18 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.