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2. Wrangling and Tidying Data
3. Importing and Joining Data
4. Visualizing Data
5. Communicating Data Science Results Effectively
6. Ethics
7. Programming
8. Modelling Data
9. Classification and Model Building
10. Model Validation and Uncertainty Quantification
11. Looking Beyond IDS