Published on: 2022-05-07 19:15:59
Categories: 28
Share:
Bayesian Statistics Specialization is a Bayesian statistics training package for forecasting and modeling published by Coursera Academy. In this training set, you will be introduced to the basics of Bayesian statistics and will strengthen your data analysis skills. This educational package includes various and scattered topics such as statistics, Bayesian statistics, Bayesian inference, R programming language, etc., and is a complete and comprehensive educational collection. This set consists of four separate courses and a completely 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 taught methods will be used in performing professional statistical analysis, building various information models and statistical forecasting.
Publisher: Coursera
Instructors: Herbert Lee, Matthew Heiner, Abel Rodriguez, Raquel Prado and Jizhou Kang
Language: English
Level: Intermediate
institution/university: University of California, Santa Cruz
Number of Courses: 5
Duration: Approximately 6 months to complete – Suggested pace of 4 hours/week
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
What background knowledge is necessary?
Prior experience with calculus (you don’t need to remember how to do it, just to understand the concepts); an introductory statistics course.
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
This Specialization contain 5 courses.
Bayesian Statistics: From Concept to Data Analysis
Bayesian Statistics: Techniques and Models
Bayesian Statistics: Mixture Models
Bayesian Statistics: Time Series Analysis
Bayesian Statistics: Capstone Project
In total, about 5.5 GB
Sharing is caring: