Turn imperfect source files into reliable analytical datasets, with preserved evidence, checked joins and repeatable workflows.
Every module includes three substantial lessons, downloadable source files, practical exercises, explained solutions and a knowledge check. Modules marked free are available under the current public access rules. Protected self-learning modules are free after registration and email verification. Publication, prerequisites and explicit private-access rules still apply.
Inspect file structure, encoding, business grain and field meaning before calculating anything.
3 lessons · 2h 55m suggested
Resolve defensible defects, quarantine uncertainty and keep a traceable record of every correction.
3 lessons · 2h 55m suggested
Load explicit schemas, transform safely and retain errors as reviewable records.
3 lessons · 2h 55m suggested
Protect grain while joining, reshaping and reconciling multiple sources.
3 lessons · 2h 55m suggested
Make an explicit snapshot workflow reproducible and design safe reruns and incremental rules.
3 lessons · 2h 55m suggested
Deliver a reproducible preparation workflow and an evidence-led handover using all three sources.
3 lessons · 2h 55m suggested
Read and practise without registering. Verify your email to use protected practice materials for free. Explore practical lessons, worked examples and projects. Follow a published path, practise the method and build work you can explain.
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