Online Course – Google Certified Professional Internship in Bayesian Statistics

Bayesian statistics for modeling and forecasting. Learn the basics and improve your data analysis skills.

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קורס אונליין - התמחות מקצועית מוסמכת בסטטיסטיקה בייסיאנית של Google

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Developing skills in statistics
  • Understanding Bayesian statistics
  • Bayesian inference
  • Programming in R
  • Data Analytics
  • Using cognitive models
  • Applying MCMC techniques
  • Working with blend models
  • Time series analysis
  • Applying a Bayesian approach to data
  • Complex data analysis
  • Writing a report on methods and results

What you will learn in the course

Courses for which the course is suitable

  • Data Analyst
  • Data Scientist
  • Statistician
  • R programmer
  • Researcher in the field of statistics
  • Bayesian statistics expert
  • Time series analyzer
  • Cognitive modeling developer
  • MCMC Expert
  • Complex data analyzer

Expertise – 5-part course series

The specialization is intended for all learners interested in developing proficiency in statistics, Bayesian statistics, Bayesian inference, R programming, and more.

Courses

  • From concept to data analysis
  • Techniques and models
  • Mixture models
  • Time series analysis

As part of the courses, you will learn Bayesian methods such as:

  • Cognitive models
  • MCMC
  • Mixture models
  • Linear dynamics

Hands-on Learning Project

The specialization trains the learner in the Bayesian approach to statistics, from the idea of ​​probability to more complex concepts.

You will learn about the philosophy of the Bayesian approach and how to apply it to common data types, and then dive deep into analyzing time series data.

The courses combine:

  • Lecture videos
  • Computer demonstrations
  • Cold readings
  • Exercises
  • Discussion boards

The final project is an opportunity for the learner to demonstrate a wide range of skills and knowledge in Bayesian statistics and apply what you have learned to real-world data.

You will review essential concepts in Bayesian statistics, learn and practice data analysis using R, perform complex data analysis on a real dataset, and compose a report on your methods and results.

Details of the courses that make up the specialization

Bayesian Statistics: From Concept to Data Analysis

Course 1
11 hours
4.6 (3,156 ratings)

What you’ll learn

  • Describe and apply the Bayesian approach to statistics.
  • Explain the key differences between Bayesian and frequentist approaches.
  • Master the basics of the R computing environment.

Skills you will acquire

  • Prediction
  • Bayesian statistics
  • Time series
  • Dynamic linear models
  • Programming in R

Bayesian Statistics: Techniques and Models

Course 2
29 hours
4.8 (481 ratings)

What you’ll learn

  • Effectively communicate the results of data analysis.
  • Use the results of statistical models to draw scientific conclusions.
  • Extend basic statistical models to account for linked observations using hierarchical models.

Skills you will acquire

  • Gibbs sample
  • Bayesian statistics
  • Bayesian inference
  • Programming in R

Bayesian Statistics: Mixed Models

Course 3
21 hours
4.5 (52 ratings)

What you’ll learn

  • Explain the basic principles behind the mixed model fitting algorithm.
  • Calculate the expectation and variance of a mixed distribution.
  • Use mixed models to solve classification and clustering problems, and provide density estimates.

Skills you will acquire

  • Mixed models
  • Bayesian statistics
  • Bayesian inference
  • Programming in R

Bayesian Statistics: Time Series Analysis

Course 4
22 hours
4.3 (14 ratings)

What you’ll learn

  • Build models that describe temporal dependencies.
  • Use R for time series analysis and forecasting.
  • Explain stationary time series processes.

Skills you will acquire

  • statistics
  • Bayesian statistics
  • Bayesian inference
  • Programming in R

Bayesian Statistics: Final Project

Course 5
11 hours

What you’ll learn

  • Demonstrate a wide range of skills and knowledge in Bayesian statistics.
  • Explain essential concepts in Bayesian statistics.
  • Apply what you have learned to real-world data.

Skills you will acquire

  • Markov model
  • Bayesian statistics
  • Mixed model
  • Programming in R

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