Coding Interview Learning Path

A structured path to master data structures and algorithms for technical interviews.

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Phase Main Topic Content & Tools Goal
1 Fundamentals
  • Choose a Programming Language
  • Big O Notation
  • Arrays & Strings
Understand time/space complexity and solve basic array problems.
2 Core Data Structures
  • Hash Table
  • Linked List
  • Stack & Queue
Implement and use common linear data structures.
3 Trees & Graphs
  • Trees (Especially Binary Trees)
  • Binary Search Tree (BST)
  • Tries (Prefix Trees)
  • Graphs
Solve traversal (BFS, DFS) and pathfinding problems.
4 Algorithmic Techniques
  • Two Pointers
  • Sliding Window
  • Recursion & Backtracking
  • Binary Search
Recognize and apply common problem-solving patterns.
5 Advanced Algorithms
  • Heap / Priority Queue
  • Dynamic Programming (DP)
  • Greedy Algorithms
Tackle complex optimization and combination problems.
6 Special Topics
  • Bit Manipulation
  • Math & Geometry
  • Advanced Data Structures
Handle niche problems and demonstrate breadth of knowledge.
7 Practice Strategy
  • Practice by Pattern
  • Maintain Consistency
  • Mock Interviews
  • Review & Optimize
Build confidence and readiness for real interviews.

Core Mindsets for Interview Success

1. Deconstruct and Conquer

Break down every complex problem into the smallest, simplest sub-problems. Master solving the small pieces before tackling the whole.

2. Pattern Recognition is Key

Most problems are variations of common patterns (e.g., two pointers, sliding window). Focus on identifying the underlying pattern, not just the surface details.

3. Master the Edge Cases

A correct solution works for *all* valid inputs. Actively think about nulls, empty arrays, single elements, and other boundary conditions. This is where bugs hide.

4. Think Out Loud

The interview is a test of your thought process. Clearly communicate your assumptions, approach, and trade-offs. Your explanation is as important as your code.