Module 1: Introduction to DSA & Problem Solving

• Importance of DSA in coding & interviews

• How to think like a programmer

• Problem-solving frameworks

• Time & Space Complexity (Big-O notation)

• Best practices for writing clean and efficient code

Module 2: Data Structures

1. Arrays

• Basic operations

• Sliding window technique

• Two-pointer technique

• Common interview problems

2. Strings

• Pattern matching

• String manipulation

• Hashing basics

3. Linked Lists

• Singly & Doubly linked lists

• Fast & slow pointers

• Reversal, loop detection

4. Stacks & Queues

• Implementation and applications

• Monotonic stack

• Queue using stacks

5. Trees

• Binary trees & BST

• Traversals

• Tree construction problems

• Lowest common ancestor (LCA)

6. Graphs

• Representation

• BFS & DFS

• Shortest path algorithms

• Connected components

7. HashMaps & Sets

• Applications in frequency counting

• Collision handling concepts

Module 3: Algorithms

1. Sorting & Searching

• Merge sort, Quick sort

• Binary search (advanced patterns)

2. Recursion & Backtracking

• Subsets, permutations

• N-Queens

• Maze problems

3. Dynamic Programming

• Memoization & Tabulation

• Classic DP problems

• Knapsack, LIS, LCS

4. Greedy Algorithms

• Interval problems

• Scheduling problems

Module 4: Competitive Programming Essentials

• Pattern identification

• Problem breakdown

• Coding speed improvement

• Debugging techniques

Module 5: Interview Preparation

• Top 100 DSA interview questions

• Company-specific problem patterns (FAANG, Product-based companies)

• Mock interviews

• Resume tips for developers

Module 6: Capstone Projects

Project 1: DSA-Based Mini Project

• Efficient real-world application using DSA

• Write optimized code for complex scenarios

Project 2: Coding Challenge Series

• Solve 50–100 structured coding problems

• Performance evaluation with reports