Coursera – Bayesian Statistics Specialization 2022-5 – Full Version

Description

The Bayesian Statistics Specialization is a training module in Bayesian Statistics for Forecasting and Modeling published by Coursera Academy. In this training package, you will learn the basics of Bayesian statistics and strengthen your skills in data analysis. This educational pack includes diverse and scattered topics such as statistics, Bayesian statistics, Bayesian inference, R programming language, etc., and is a complete and comprehensive educational collection. This package consists of four separate courses and a fully practical project, and during its training process, different Bayesian statistical methods such as ex-conjugate distribution, Monte Carlo Markov chain, mixture models, dynamic linear modeling. And… you will learn. All the methods taught will be used to perform professional statistical analysis, build various information models and make statistical forecasts.

What you will learn in the Bayesian Statistics specialization

Bayesian inference
Time series forecasting
Hierarchical Bayesian modeling
Data Science
R programming language
Analysis and analysis of information
Bayesian statistics and statistics and its different methods
Gibbs sampling
Markov model
Mix model
Forecast
Dynamic Linear Modeling
Time series

Course specifications

Editor: Coursera
Instructors: Herbert LeeMatthew Heiner, Abel Rodriguez, Raquel Prado and Jizhou Kang
French language
Intermediate level
institution/university: University of California, Santa Cruz
Number of Courses: 5
Duration: Approximately 6 months to complete – Suggested pace of 4 hours/week

Course included:

Course 1

Bayesian statistics: from concept to data analysis

Course 2

Bayesian statistics: techniques and models

Course 3

Bayesian statistics: mixture models

Course 4

Bayesian Statistics: Time Series Analysis

Course 5

Bayesian Statistics: Capstone Project

Specialization prerequisites in Bayesian statistics

What prior knowledge is needed?

Previous experience with calculation (you don’t need to remember how to do it, just to understand the concepts); an introductory course in statistics.