This repository is a lightweight book for refreshing core concepts ahead of technical interviews. Each chapter focuses on a single idea, demonstrates it with Python, and closes with interview-ready checkpoints.
- Warm up with Part 01 to rebuild intuition before diving into problem drills.
- Refer back to the data-structure and appendix chapters when you need a quick reminder during practice.
- Take notes inside each chapter—treat this as a living workbook tailored to your learning style.
- 01 · Introduction and Motivation
- 02 · How Computers Execute Code
- 03 · Where Algorithms Show Up
- 04 · Complexity Basics
- 05 · Math Toolkit for Algorithms
- 01 · Data Structures Overview
- Linear Structures
- Hash-Based Structures
- Trees
- Graphs
- Heaps & Priority Queues
- Advanced Topics
- 01 · Recursion and Backtracking
- 02 · Divide and Conquer
- 03 · Sorting and Searching
- 04 · Greedy Strategies
- 05 · Dynamic Programming
- 06 · Graph Traversal and Pathfinding
- 07 · Canonical Problem Walkthroughs
- 08 · Review Checklists and Quick Guides
- 01 · Problem-Solving Frameworks and Communication
- 02 · Progressive Practice Plan
- 03 · Post-Interview Retrospectives
Use the playbook to prepare before, during, and after interview loops: follow the Solve→Code→Validate framework, schedule practice with the four-week plan, and record learnings with the retrospective template.
Before adding or editing content, read AGENTS.md for the project layout, writing conventions, and review checklist.