Description
Bayesian Statistics Specialization is a Bayesian statistics training series for forecasting and modeling published by Coursera Academy. In this educational series, he will get acquainted with the basic principles of Bayesian statistics and will strengthen his data analysis skills. This educational collection 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 series consists of four separate courses and a completely practical project, and during the educational process, different methods of Bayesian statistics such as prior conjugate distribution, Monte Carlo Markov chain, mixture models, dynamic linear modeling And you will learn… All the taught methods will be used in performing professional statistical analysis, building different information models and statistical forecasting.
What you will learn in the Bayesian Statistics Specialization course:
- Bayesian inference
- Time Series Forecasting
- Bayesian hierarchical modeling
- data scienceData Science)
- R programming language
- Analysis and review of information
- Bayesian statistics and statistics and its various methods
- Gibbs sampling
- Markov model
- mixed model (Mixture Model)
- Forecasting
- dynamic linear modeling
- Time series (Time series)
Course details
Publisher: Coursera
teacher: Herbert Lee ,Matthew Heiner ,Abel Rodriguez ,Raquel Prado And Jizhou Kang
English language
Providing institution/university: University of California (University of California Santa Cruz)
Education level: Intermediate
Number of courses: 5
Duration of training: assuming 4 hours of work per week, about 6 months
Courses available in the Bayesian Statistics Specialization collection
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
Course prerequisites
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.
Course images
Sample video of the Bayesian Statistics Specialization course
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
This collection includes 5 different courses.
download link
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
Password file(s): www.downloadly.ir
Size
About 5.5 GB in total
Be the first to comment