1Part 1: Foundations of Data Science and the Data-Driven Mindset
8Statistical Inference and Experimental Design
2The Foundations of Data Science: Computational and Inferential Thinking
9Supervised Learning I: Regression and Classification Foundations
3The Data Scientist's Toolkit: Programming, Analysis, and Collaboration
10Supervised Learning II: Non-Linear Models
4Data Acquisition and Management: Relational Databases and SQL
11Unsupervised Learning and Advanced Tabular Modeling
5Data Ethics, Governance, and Responsible AI
12Model Validation and Trustworthy AI
6Data Visualization and Business Intelligence Communication
13About Author
7Part 2: Core Machine Learning and Statistical Inference
