How to revise Tools in Data Science
Tools in Data Science questions reward clear reasoning as well as a final answer. This revision guide is a starting point for using the available papers; it is not the official syllabus or a promise about future exams.
Revision focus
Data formats; command-line workflows; APIs; reproducible data analysis
Useful prior knowledge
Python basics, files and HTTP concepts
Common mistakes
Assuming that a command or data conversion preserves types and encodings
Use these papers effectively
Test each transformation on a small input and inspect the output schema. Record the command and environment needed to reproduce the result. After checking a solution, solve the question again without looking and record the specific step you missed.
Revision guidance only. Check your current official course materials for the assessed syllabus.