Course Content

1. Introduction to DSA
Understand the importance of data structures and algorithms in problem solving and software development.

2. Time & Space Complexity
Learn Big-O notation to analyze algorithm efficiency. Compare performance based on execution time and memory usage.

3. Arrays
Understand linear data storage. Perform operations like insertion, deletion, searching, and traversal.

4. Strings (DSA Perspective)
Solve string manipulation problems. Learn pattern matching and optimization techniques.

5. Recursion
Understand function calls within functions. Solve problems using recursive thinking and backtracking.

6. Searching Algorithms
Learn Linear Search and Binary Search. Understand when and how to use optimized searching methods.

7. Sorting Algorithms
Study Bubble, Selection, Insertion, Merge, and Quick Sort. Compare sorting techniques based on efficiency.

8. Linked List
Understand dynamic data storage using nodes. Learn singly and doubly linked list operations.

9. Stack
Learn LIFO (Last In First Out) structure. Implement stacks using arrays and linked lists.

10. Queue
Understand FIFO (First In First Out) structure. Implement simple queue and circular queue.

11. Hashing
Learn hash tables and hash functions. Understand fast data retrieval using key-value mapping.

12. Trees
Understand hierarchical data structures. Learn binary trees and tree traversals (Inorder, Preorder, Postorder).

13. Binary Search Tree (BST)
Learn insertion, deletion, and searching in BST. Understand how trees improve search efficiency.

14. Heap
Understand min-heap and max-heap structures. Learn priority queue implementation.

15. Graphs
Study graph representation using adjacency list and matrix. Learn BFS and DFS traversal algorithms.

16. Greedy Algorithms
Understand decision-making approach to solve optimization problems efficiently.

17. Dynamic Programming (Basics)
Learn how to solve complex problems by breaking them into smaller subproblems.