Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python

Tech Challenge of the Postgraduate in Data Analytics, from FIAP, analyzing Brent Oil price data, in comparison with historical, economic and societal data, integrating correlation and causality analyzes of items with prices, as well as developing a model forecast and an importance analysis through information gain from a forest model (XGBoost)

Leverage data analytics to identify "Hot Leads" and sculpt personalized strategies for maximum conversion potential, propelling X Education to new heights of success.

Data Science Case Study: To help X Education select the most promising leads (Hot Leads), i.e. the leads that are most likely to convert into paying customers.