Books¶
Overview¶
This page lists widely recommended books across the Engineering OS curriculum. Use it as a starting library—not an exhaustive catalog.
Why This Exists¶
Long-form books build durable mental models beyond blog-sized takes.
How It Works¶
Pick one book per quarter, take notes, and tie chapters back to projects or LeetCode/system design practice.
Curated list¶
| Topic | Book | Notes |
|---|---|---|
| Algorithms | Introduction to Algorithms (CLRS) | Rigorous; use as reference |
| Systems | Designing Data-Intensive Applications (Kleppmann) | Modern data systems primer |
| Networking | Computer Networking: A Top-Down Approach | Classroom standard |
| Architecture | Building Microservices (Newman) | Practical service boundaries |
| AI / ML breadth | Hands-On Machine Learning (Géron) | Implementation-oriented |
Key Concepts¶
Read actively
Summarize each chapter in your own words and link to one real system you have used.
Code Examples¶
Skim chapter -> implement one exercise -> write 5 bullet notes -> add to flashcards
Interview Questions¶
How do you choose what to read next?
Match gaps in upcoming interviews or on-the-job pain points; alternate depth (textbook) with breadth (anthology blogs).
Practice Problems¶
- Finish one chapter of DDIA and diagram a concept you did not know before
- Teach a chapter summary to a peer in 15 minutes
Resources¶
- Open Library — discoverability
- Local libraries and inter-library loans for cost access