Data Science

Data Science

Data science is using data to answer questions and inform decisions. Not just "what happened" but "why did it happen, will it happen again, and what should we do about it?" The work spans exploratory analysis, statistical modeling, prediction, causal inference, and communicating findings to people who need to act on them.

Introduction Setup

Descriptive Analysis and Verification

First Prediction Model

Multi-Source Analysis and Inferential Depth

Classification and Imbalanced Evaluation

Method-Driven Preparation and Leakage Prevention

Question Typology Ownership

AI Infrastructure Introduction

First MCP Connection: DuckDB Integration

Causal Inference: Loyalty Program Evaluation

Causal Validation: Sensitivity, Delegation, and Cross-Tool Verification