Principles of Data Science

Table of Contents

1. Data Science Terminology
2. Types of Data
3. The Five Steps of Data Science
4. Basic Mathematics
5. Impossible or Improbable – A Gentle Introduction to Probability
6. Advanced Probability
7. What are the Chances? An Introduction to Statistics
8. Advanced Statistics
9. Communicating Data
10. How to Tell if Your Toaster is Learning – Machine Learning Essentials
11. Predictions Don't Grow on Trees, or Do They?
12. Introduction to Transfer Learning and Pre-trained Models
13. Mitigating Algorithmic Bias and Tackling Model and Data Drift
14. AI Governance
15. Navigating Real-World Data Science Case Studies in Action