Overview
Context
Bayesian data analysis is an increasingly popular method of statistical inference, used to determine conditional probability without having to rely on fixed constants such as confidence levels or p-values.
In this Bayesian Data Analysis in Python course offered by Data Camp, you’ll learn how Bayesian data analysis works, how it differs from the classical approach, and why it’s an indispensable part of your data science toolbox.
You’ll get to grips with A/B testing, decision analysis, and linear regression modeling using a Bayesian approach as you analyze real-world advertising, sales, and bike rental data. Finally, you’ll get hands-on with the PyMC3 library, which will make it easier for you to design, fit, and interpret Bayesian models.
Programme Structure
Chapters
- The Bayesian way
- Bayesian estimation
- Bayesian inference
- Bayesian linear regression with pyMC3
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Campus Location
- New York City, United States
Disciplines
Statistics View 109 other Short Courses in Statistics in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is suitable for beginners and experienced data scientists alike.
- This course is an invaluable asset for many job roles that require data analysis skills, including data scientists, statisticians, business analysts, and marketing professionals.
PREREQUISITES:
- Introduction to Statistics in Python
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions