FAQs
- To develop proficiency in R for data analysis, statistical computing, and machine learning
- To perform data cleaning, transformation, and visualisation using dplyr and ggplot2
- To apply statistical and probability concepts for meaningful data insights
- To build and evaluate machine learning models like Linear & Logistic Regression, Decision Trees, etc.
- To understand Decision Trees, including entropy, CART, and attribute selection methods
- To solve real-world business problems through hands-on case studies (e.g., churn prediction, customer segmentation)
- MIS professionals
- Business intelligence professionals
- Data scientists
- Students
- Business analysts
- Project managers
- Entrepreneurs


































