Data Structures & Algorithms

Master DSA.
Think like a problem solver.

Build a stronger foundation in data structures and algorithms. Learn the concepts, recognize problem-solving patterns, and practise turning your ideas into efficient solutions.

Explore DSA Topics Open DSA Sheet

Understand the approach. Write the code. Learn from every attempt.

problem_solving.py

def solve(problem):

# Understand the input

constraints = understand(problem)

# Find a suitable approach

approach = choose_pattern(problem)

solution = implement(approach)

test(solution)

return solution

# Progress comes from practice.

keep_learning = True

🧠 Problem Solving Improve your thinking process 🧩 DSA Topics Explore concepts and patterns 📝 DSA Sheet Practise and track problems

Build your foundation

Explore DSA topics.

Start with the fundamentals, then work towards more complex structures and algorithmic techniques.

📦

Arrays & Strings

Learn indexing, traversal, searching, frequency counting, and common array and string techniques.

Fundamentals Beginner

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🔑

Hashing

Use hash maps and sets to manage frequency counts, fast lookups, duplicates, and related problems.

Data structure Lookup

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↔️

Problem-Solving Patterns

Recognize two pointers, sliding window, and prefix sum techniques that help structure efficient solutions.

Patterns Optimization

Explore patterns

🔗

Linked Lists

Understand nodes, pointers, list traversal, insertion, deletion, and common linked-list problems.

Data structure Pointers

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📚

Stacks & Queues

Learn LIFO and FIFO structures, their operations, and how they apply to traversal and ordering problems.

Data structure Operations

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🔍

Searching & Sorting

Understand binary search, sorting strategies, and how ordered data can help solve problems efficiently.

Algorithms Efficiency

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🔁

Recursion & Backtracking

Break a problem into smaller calls and explore decision paths while learning base cases and backtracking.

Problem solving Recursion

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🌳

Trees

Explore tree structure, binary trees, traversal methods, recursion, and binary search tree fundamentals.

Data structure Traversal

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🕸️

Graphs

Understand vertices, edges, graph representations, BFS, DFS, and common graph traversal problems.

Data structure Traversal

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🧮

Dynamic Programming

Learn to identify overlapping subproblems and explore memoization, tabulation, and state transitions.

Optimization Advanced

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⛰️

Heaps & Priority Queues

Understand priority-based retrieval and the use of heaps in selection and scheduling problems.

Data structure Ordering

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🎯

Greedy Algorithms

Explore problems where making a locally optimal choice can lead to a globally optimal solution.

Algorithms Strategy

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A practical sequence

Build your DSA roadmap.

A suggested order for learning. Move forward as you become comfortable with each stage.

Build the basics

Arrays, strings, complexity analysis, and fundamental searching and sorting.

Learn core structures

Hashing, linked lists, stacks, queues, trees, and heaps.

Recognize patterns

Two pointers, sliding window, recursion, backtracking, graphs, and dynamic programming.

Practise & reflect

Solve problems, compare approaches, review mistakes, and revisit challenging questions.

Beyond writing code

Improve how you think through problems.

Progress in DSA isn’t only about the number of questions you solve. Learn to understand the problem, compare approaches, evaluate complexity, and reflect on what you missed.

Explore the problem-solving framework →

Understand the input, output, and constraints.

Explore possible approaches before coding.

Compare time and space complexity.

Review mistakes and identify reusable patterns.

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