🧠 The Ultimate DSA Roadmap with Python (Beginner to Advanced)

Are you ready to master Data Structures and Algorithms (DSA) with Python? Whether you're preparing for coding interviews, improving your problem-solving skills, or building a solid foundation in computer science, this guide is for you.

Over the next 6–8 months, follow this structured, phase-by-phase roadmap and become a DSA pro—one step at a time.

✅ Phase 1: Foundations (Weeks 1–4)

🎯 Goal:

Build strong programming basics and understand time-space complexity.

📌 Topics to Study:

Python Fundamentals

• Variables, Data Types
• Conditions (if, else)
• Loops (for, while)
• Functions
• List Comprehensions
• String Operations
• Error Handling (try, except)

Object-Oriented Programming (Optional for now but useful later)

• Classes & Objects
• Inheritance, Polymorphism

Recursion Basics

• What is recursion?
• Base Case & Recursive Case
• Examples: Factorial, Fibonacci, Sum of Array, etc.

Time & Space Complexity

• Big O notation
• Analyzing loops
• Best, Average, Worst cases

🛠️ How to Study:

• Watch tutorials from freeCodeCamp Python Course
• Practice Python basics on:
  • HackerRank – Python
  • Exercism.io

🧠 Focus:

• Write code without copying
• Get comfortable using loops, arrays, and recursion

✅ Phase 2: Basic Data Structures (Weeks 5–8)

🎯 Goal:

Understand how basic data structures work and how to implement them.

📌 Topics:

Arrays & Strings

• Reverse, Rotate, Frequency Count, Palindrome

Stacks

• Push, Pop, Peek, Infix to Postfix

Queues

• Normal Queue
• Circular Queue
• Deque (Double-ended queue)

Linked Lists

• Singly Linked List
• Doubly Linked List
• Detect Cycle

Hash Table / Dictionary

• Key-value storage
• Use cases like frequency counting, lookups

🛠️ Practice:

• Implement each structure from scratch
• Solve basic problems from:
  • LeetCode – Easy Problems
  • GFG – Must Do DSA

✅ Phase 3: Recursion & Backtracking (Weeks 9–10)

📌 Topics:

Recursion Deep Dive

• Factorial, Fibonacci, Power, Subset Sum

Backtracking

• Permutations
• Combinations
• N-Queens Problem
• Sudoku Solver

📚 Resources:

• Backtracking Pattern - NeetCode
• YouTube: Backtracking Playlist - Take U Forward

✅ Phase 4: Searching & Sorting (Weeks 11–13)

📌 Topics:

Binary Search (and Variations)

• First/Last Occurrence
• Rotated Sorted Array

Sorting Algorithms

• Bubble, Selection, Insertion
• Merge Sort
• Quick Sort
• Counting Sort

🛠️ How to Practice:

• Implement each sort manually
• Do 10–15 problems using binary search logic

📚 Resources:

• Binary Search - NeetCode
• Sorting Algorithms Visualized

✅ Phase 5: Math & Bit Manipulation (Weeks 14–15)

📌 Topics:

Math

• Prime Numbers
• Sieve of Eratosthenes
• GCD, LCM, Modular Arithmetic

Bit Manipulation

• AND, OR, XOR
• Checking if a number is even/odd
• Count set bits
• Bitmasking

📚 Resources:

• Bit Manipulation from NeetCode / Aditya Verma
• GFG Math Topic List

✅ Phase 6: Trees (Weeks 16–18)

📌 Topics:

Binary Trees

• Traversals: Inorder, Preorder, Postorder
• Level Order, DFS, BFS

Binary Search Tree (BST)

• Insertion, Deletion, Search

Tree Problems

• Height, Diameter, LCA
• Mirror of a tree, Balanced Tree

📚 Practice:

• 20+ Tree problems on LeetCode
• Visualizations: VisualGo Tree

✅ Phase 7: Graphs (Weeks 19–22)

📌 Topics:

Graph Representations

• Adjacency List / Matrix

Traversals

• DFS, BFS

Advanced Graphs

• Dijkstra's, Floyd-Warshall
• Union-Find / Disjoint Set
• Topological Sorting

📚 Practice:

• LeetCode Graph Tag
• GFG Graph Playlist

✅ Phase 8: Advanced Topics (Weeks 23–28)

📌 Topics:

Heaps / Priority Queues

• Min-Heap, Max-Heap

Tries

• Word Search, Prefix Tree

Sliding Window Technique

• Max sum subarray, Longest substring

Two Pointers

• Sorted arrays, Palindromes

Greedy Algorithms

• Activity selection, Fractional knapsack

Dynamic Programming (DP)

• Fibonacci, Knapsack, LIS, LCS
• Memoization, Tabulation

📚 Must-Watch:

• DP by Aditya Verma (YouTube)
• NeetCode Dynamic Programming