Data Science Hacks – Google Causal Impact , Inferring Causal Impact with Google’s Causal Impact Package.
Course Description
Welcome to our Google Causal Impact Course.
This course I’ll teach you how to use the google’s package Causal Impact in your on job or personal projects.
The Causal Impact model developed by Google works by fitting a bayesian structural time series model to observed data which is later used for predicting what the results would be had no intervention happened in a given time period. The idea is to used the predictions of the fitted model (depicted in blue) as a reference to what probably would had been observed with no intervention taking place.
After this course you will have a powerful tool, to measure (with statistical significance):
* The extra number of sales / app downloads / clicks / web site visits caused by a marketing campaign
* The ROI of a Marketing Campaign
* The effect of a promotion over demand
* Any change of behavior in a series, caused by a known event
Who this course is for:
- Data Analysts and Data Science Students
- Anyone interested in causal inference techniques and data analysis with python
