Data Analytics¶
University-level data analytics course materials — notes, exercises, quizzes, and hands-on projects in Python, R, and Excel.
Course Flow¶
- Read the chapter notes.
- Work through the matching exercise set.
- Test yourself in the quiz hub.
- Build the matching project(s) to apply the concepts end-to-end.
Chapters¶
| Chapter | Focus | Start |
|---|---|---|
| 01 | Data & Attribute Types | What Can We Do With Data? |
| 02 | Descriptive Statistics | Descriptive Statistics |
| 03 | Descriptive Multivariate Analysis | Multivariate Analysis |
| 04 | Data Quality and Preprocessing | Data Quality & Preprocessing |
| 05 | Clustering | Clustering |
| 06 | Frequent Pattern Mining | Frequent Pattern Mining |
| 07 | Classification | Classification |
| 08 | Course Summary | Summary & Cheat Sheet |