Data Structures & Algorithms (DSA) Learning Path

A comprehensive roadmap to build a strong DSA foundation for interviews and competitive programming.

Back to Roadmap
Phase Main Topic Content Goal
1 Fundamentals
  • Choose a Programming Language
  • Big O Notation
  • Basic Mathematics
 Build a strong foundation in a language and algorithmic complexity analysis.
2 Data Structures
  • Arrays & Strings
  • Linked Lists
  • Stacks & Queues
  • Hashing
 Understand and implement basic linear data structures.
3 Algorithms
  • Sorting & Searching
  • Recursion & Backtracking
  • Two Pointers Technique
  • Sliding Window Technique
 Master core algorithms and problem-solving techniques.
4 Advanced Topics
  • Trees & Graphs
  • Greedy Algorithms
  • Dynamic Programming (DP)
  • Bit Manipulation
 Tackle more complex problems with advanced structures and algorithms.
5 Interview Preparation
  • Top Interview Questions
  • Practice by Company
  • GFG's DSA Course
  • Mock Interviews
 Apply learned knowledge in a real interview setting.

Core Mindsets for DSA Mastery

1. Abstraction is Key

Focus on what a data structure *does* (its API and time complexity) before worrying about how it's implemented. Understand the concept first.

2. Everything is a Trade-off

No data structure is perfect for all situations. Always analyze the time vs. space complexity. Is fast insertion more important than fast lookup for this problem?

3. Recognize the Pattern

Most algorithmic problems are variations of a few core patterns (e.g., two pointers, sliding window, BFS/DFS). Practice identifying the underlying pattern.

4. Visualize First, Code Second

Before writing code for trees, graphs, or linked lists, draw them on paper or a whiteboard. Trace your algorithm visually to catch logic errors before you type.