What is a reproducible analytical pipeline (RAP), writing “good code” and creating a reproducible report.
Participants should gain an awareness of the importance of reproducibility in their work. Learners will also gain experience of linting code in Python and using parameterised reports in R markdown.
- Represent pipelines and identify opportunities to automate;
- Consider adherence to a programming style guide;
- Use linting software to standardise Python scripts;
- Use parameterised R markdown reports to improve the efficiency of report production.
E learning – Not available
Self learning – Not available
Face to face – Available
Basic familiarity with Python and R programming is assumed.
To discuss booking this course for remote delivery, please contact the Data Science Campus Faculty.