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Coursera

Bayesian Statistics

University of California, Santa Cruz via Coursera Specialization

Overview

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This Specialization is intended for all learners seeking to develop proficiency in statistics, Bayesian statistics, Bayesian inference, R programming, and much more. Through four complete courses (From Concept to Data Analysis; Techniques and Models; Mixture Models; Time Series Analysis) and a culminating project, you will cover Bayesian methods — such as conjugate models, MCMC, mixture models, and dynamic linear modeling — which will provide you with the skills necessary to perform analysis, engage in forecasting, and create statistical models using real-world data.

Syllabus

Course 1: Bayesian Statistics: From Concept to Data Analysis
- Offered by University of California, Santa Cruz. This course introduces the Bayesian approach to statistics, starting with the concept of ... Enroll for free.

Course 2: Bayesian Statistics: Techniques and Models
- Offered by University of California, Santa Cruz. This is the second of a two-course sequence introducing the fundamentals of Bayesian ... Enroll for free.

Course 3: Bayesian Statistics: Mixture Models
- Offered by University of California, Santa Cruz. Bayesian Statistics: Mixture Models introduces you to an important class of statistical ... Enroll for free.

Course 4: Bayesian Statistics: Time Series Analysis
- Offered by University of California, Santa Cruz. This course for practicing and aspiring data scientists and statisticians. It is the fourth ... Enroll for free.

Course 5: Bayesian Statistics: Capstone Project
- Offered by University of California, Santa Cruz. This is the capstone project for UC Santa Cruz's Bayesian Statistics Specialization. It is ... Enroll for free.

Courses

Taught by

Abel Rodriguez, Herbert Lee, Jizhou Kang, Matthew Heiner and Raquel Prado

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