Data preparation - cleaning of data set
2. Exploratory Data Analysis - to perform descriptive analysis for categorical data and determine which attributes most contribute towards churn
3. Algorithm model implementation and validation - Decision Tree, Random Forest & Logistic Regression (also include optimization model). Must evaluate its results and interpret their significance. Comprehensively explain the output of the model and its internal parameters.
4. Analysis & Recommendations - What happened? Is it what was expected? What were the surprises/anomalies? Must also include comparison between the models