1. Introduction to Data Structures
Fundamentals of organizing data, Abstract Data Types (ADTs), and the crucial role of data structures in software development.
2. Algorithmic Efficiency & Complexity
Understanding Big-O notation, calculating time and space complexity, and analyzing worst, average, and best-case scenarios.
3. Stack
The LIFO (Last In, First Out) principle, push and pop operations, and real-world applications like expression evaluation.
4. Queue
The FIFO (First In, First Out) principle, enqueue and dequeue operations, circular queues, and priority queues.
5. List and Linked List
Dynamic memory allocation, traversing, inserting, and deleting nodes in singly, doubly, and circular linked lists.
6. Recursion
Mastering base cases, recursive function calls, tail recursion, and tracing classical problems like Tower of Hanoi.
7. Trees
Hierarchical structures: Binary trees, Binary Search Trees (BST), AVL trees, and traversal techniques.
8. Sorting
Comprehensive guide to arranging data using Bubble, Insertion, Selection, Merge, Quick, and Heap sort algorithms.
9. Searching and Hashing
Techniques for finding data quickly: Linear vs. Binary search, Hash functions, Hash tables, and collision resolution.
10. Graphs
Network models: Vertices, edges, representation (adjacency matrix/list), and traversal algorithms like BFS and DFS.
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