Learning Track · 5 Modules · 17 Lessons · 13 Exercises · 14h
The Data engineering curriculum
A pipeline is a promise about data that has to keep being true tomorrow. Read a messy file without a library, quarantine what is wrong instead of dropping it, put it in a table you can query, then make the whole thing re-runnable and checkable.
Prerequisites & Preparation
Prerequisites: Python 3.10+ standard library
Recommended: Introduction to programming (Modules 00–01)
Scope: Engineers building idempotent pipelines, quarantine validators, SQLite storage, and data contracts.
Track Architecture
- [handling] Handling data: Reading it, cleaning it, and putting it somewhere you can ask questions.
- [pipelines] Moving data: Making the whole thing re-runnable, and knowing when it has quietly stopped working.
Handling data
Reading it, cleaning it, and putting it somewhere you can ask questions.
Moving data
Making the whole thing re-runnable, and knowing when it has quietly stopped working.