Welcome to our training catalog. All courses are provided in-house and the courses listed below can be mixed to meet your needs.

Please contact us to discuss what courses would best match your requirements and if you have any questions on specific courses or course categories.

 

Bayesian Data Analysis

Bayesian Data Analysis Image

Bayesian analysis is sometimes maligned by data analysts, due in part to the perceived element of arbitrariness associated with the selection of a meaningful prior distribution for a specific problem and the (former) difficulties involved with producing posterior distributions for all but the simplest situations. On the other hand, we have heard it said that “while classical data analysts need a large bag of clever tricks to unleash on their data, Bayesians only ever really need one.” With the advent of efficient numerical samplers, modern data analysts cannot shy away from adding the Bayesian arrow to their quiver. In this course, we will introduce the basic concepts underpinning Bayesian analysis, and present a small number of examples that illustrate the strengths of the approach.

Category:
Advanced Topics
Tags:
Special Topics in AI/ML/DS, Instructor Led, Learning by Doing, Self Guided
Product Code:
ST-6
Course Duration (hours):
12

Bayesian Data Analysis

Bayesian Data Analysis Image

Bayesian analysis is sometimes maligned by data analysts, due in part to the perceived element of arbitrariness associated with the selection of a meaningful prior distribution for a specific problem and the (former) difficulties involved with producing posterior distributions for all but the simplest situations. On the other hand, we have heard it said that “while classical data analysts need a large bag of clever tricks to unleash on their data, Bayesians only ever really need one.” With the advent of efficient numerical samplers, modern data analysts cannot shy away from adding the Bayesian arrow to their quiver. In this course, we will introduce the basic concepts underpinning Bayesian analysis, and present a small number of examples that illustrate the strengths of the approach.