Tutorial series
Data Engineering Mastery Platform
A study coach for data-engineering exams: how it started, what broke, what was decided, and what the evidence says — explained in plain words.
Case study: Data Engineering Mastery Platform
- Part 1
Repo structure and the spec-driven method
Follow one learner from signup to study plan while learning how specs, ADRs, and a Makefile keep a year-long build coherent.
- Part 2
The learning engine: how the app knows what Priya needs
Six small algorithms decide what she studies, when she reviews, and whether she's ready — real code, hand-worked numbers, zero AI.
- Part 3
API and data model: what each endpoint does for Priya
Follow her clicks through sixteen router groups: what each API does, where her data lives, and why writes are decided server-side.
- Part 4
The content pipeline: how Priya's curriculum gets built
Follow one syllabus from raw PDF to validated, searchable lesson: seven stages, idempotent re-runs, ordered validators, gated publishing.
- Part 5
Knowledge systems and capstone: search, agents, and principles
How Priya finds things, how agents use the same backend, every term defined, and the principles worth stealing — with what I'd investigate next.
- Part 6
Guided demo: one real hour inside the app
Register, tour, practice, and break things on the live build: what works first-hand, what fails, and what each failure teaches.