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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Bayesian Statistics will help the participant to understand the necessary bayesian concepts from a practical point of view for better decision making. The participants will learn how the Bayesian approach is used to estimate likely event outcomes or probabilities using datasets. This Bayesian Statistics course is being offered by IIM Bangalore. This Bayesian Statistics course is delivered through their digital learning platform IIMBx.
The duration of this Bayesian Statistics course is six weeks. The participants will learn the foundations of bayesian concepts, contrasting them with classical statistics. The curriculum is being bifurcated into theoretical and empirical segments. Once the participants have completed the Bayesian Statistics course they will have a comprehensive understanding of the Bayesian approach.
The Highlights
- Six week duration
- 3-4 hours per week
- In-depth analysis of Bayesian vs. Classical Statistics
- Hands-on experience with Monte Carlo methods
- Practical application using R and OPENBUGS
- Insights into Bayesian linear and hierarchical models
Programme Offerings
- 6 week course
- Expert Faculty
- Offered by IIM Bangalore
Courses and Certificate Fees
| Certificate Availability |
|---|
| no |
What you will learn
Through this Bayesian Statistics Course, the participants will learn the difference between bayesian statistics and classical statistics. This course will help the participants to learn about the foundation of bayesian concepts.
Who it is for
The target audience for the Bayesian Statistics Course includes:
The Syllabus
What is Bayesian Statistics and How it is different than Classical Statistics
- Foundations of Bayesian Inference
- Bayes theorem
- Advantages of Bayesian models
- Why Bayesian approach is so important in Analytics
- Major densities and their applications
Bayesian analysis of Simple Models
- Likelihood theory and Estimation
- Parametrizations and priors
- Learning from binary models
- Learning from Normal Distribution
Monte Carlo Methods
- Basics of Monte carol integration
- Basics of Markov chain Monte Carlo
- Gibs Sampling
Computational Bayes
- Examples of Bayesian Analytics
- Introduction to R and OPENBUGS for Bayesian analysis
Bayesian Linear Models
- Context for Bayesian Regression Models
- Normal Linear regression
- Logistic regression
Bayesian Hierarchical Models
- Introduction to Multilevel models
- Exchangeability
- Computation in Hierarchical Models
Instructors
IIM Bangalore Frequently Asked Questions (FAQ's)
The duration of the Bayesian Statistics Course is six weeks, with an estimated 3–4 hours of study per week.
No, there are no prerequisites required for enrolling in this course.
Yes, Once the participants have successfully completed the course, they will receive the certificate.
The course utilises R and OPENBUGS for Bayesian analysis.
No, there is no financial aid available.