Predictive analytics (PA) is on everyone's lips. But what is it really all about? Discover its principle, implementation, typical pitfalls and good practices. Learn about data wrangling and munging, a crucial step in predictive analytics. An overview of the most commonly used models is also presented.
A Primer on Predictive Analytics
Upon completion of this module, participants will be able:
- To understand what predictive analytics (PA) is about
- To master the general principles underlying the realization of a PA study (data munging, data selection, etc.)
- To understand the key issues to address in a PA study and common pitfalls
- To know about the most commonly used modelling techniques in PA
This applied training session is aimed at people who need to understand the steps involved in the development of a predictive model.
This module introduces key concepts in modelling. It assumes that participants either have no previous knowledge of statistics or that they have not used statistics for a long time.
- Goals and context of use of PA
- Principle underlying PA
- Measuring the predictive ability of a model
- Setting Up a PA Study
- Defining the goal
- Selecting and preparing the data
- Choosing and testing models
- Overwiew of the most commonly used models
- Mistakes to avoid
- Good practices
Recommended Duration: 1 day