Principles and Foundations of Data Science
Companion site for the book by M. Tamer Özsu — errata, review questions, and slides.
Review Questions
Review questions are organized by chapter, following the structure of the book. They are intended for self-study and for instructors assembling problem sets; solutions are not posted here.
| Chapter | Title |
|---|---|
| 1 | Introduction |
| 2 | What is Data Science? |
Part I. Technical Foundations
| Chapter | Title |
|---|---|
| 3 | Computing Foundations |
| 4 | Mathematics and Optimization Foundations |
| 5 | Statistics and Machine Learning Foundations |
Part II. The Four Pillars
| Chapter | Title |
|---|---|
| 6 | Data Engineering |
| 7 | Data Analytics |
| 8 | Data Protection |
| 9 | Data Science Ethics |
Part III. Context and Process
| Chapter | Title |
|---|---|
| 10 | The Social and Policy Context |
| 11 | Data Science Lifecycle |
Part IV. Practice
| Chapter | Title |
|---|---|
| 12 | Data Science Applications—Examples |
| 13 | Data Science System Architecture |
Part V. Synthesis and Outlook
| Chapter | Title |
|---|---|
| 14 | Conclusions |