The 28-Day Engineering Plan
A focused 28-day program across five tracks — Data Engineering, Machine Learning, AI & LLMs, OOP & Programming, and System Design. One deep topic per day.
How the plan is structured
Five rotating tracks, interleaved so back-to-back days never share a track:
- Data Engineering — Spark, Kafka, lakehouse, streaming, modelling, governance
- Machine Learning — trees, embeddings, evaluation, MLOps
- AI & LLMs — transformers, RAG, agents, fine-tuning, evals, multimodal
- OOP & Programming — design patterns, SOLID, concurrency, memory, idiomatic Python / C#
- System Design — sharding, consistency, queues, caching, multi-region case studies
Each day stands alone, but the sequence builds. You can run it back-to-back over 28 days, or stretch it out — the structure stays the same.
Where to start
The full schedule, day-by-day topics, and direct links to every deep dive live on the dedicated plan page:
Why this format
A lot of "interview prep" content is shallow — a checklist of topics with surface-level summaries. This program leans the other way: fewer topics, more depth. Every day's notes go into why a system was built a certain way, the tradeoffs that fell out, and the failure modes you only see in production.
If you work through it honestly, you'll come out with stronger mental models in five domains at once — and a pile of notes you can come back to.
Mid-article nudge
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