Causal Inference in Python. Causal Relationships in IT Development

How many customers will an additional dollar spent on online advertising attract? Which customers will only buy when given a discount coupon? How to determine the optimal pricing strategy? The best way to find out how the levers we have at our disposal affect the business metrics we want to achieve is causal inference.
Mateusz Fakur, a senior data analysis specialist at Nibank, discusses the largely untapped potential of causal inference for assessing consequences and effects. Managers, data processing specialists, and business analysts will get acquainted with classical methods of visual inference, such as randomized controlled trials (A/B tests), linear regression, propensity score matching, synthetic controls, and difference in differences. Each method is accompanied by a real-life example.