Data Structure Course Overview

This comprehensive course covers Data Structure concepts such as follow :

• Introduction to Data Structures
  • *Need and applications of data structures
  • *Abstract Data Types (ADT)
  • *Complexity analysis:
  • *Time and space complexity
  • *Big-O, Ω (Omega), and Θ (Theta) notations
  Arrays and Strings
*Representation of arrays in memory
*Operations on arrays (traversal, insertion, deletion, searching, sorting)
*Multidimensional arrays
*Strings and string operations

• Functions and Recursion
• Linked Lists
*Singly linked list: creation, insertion, deletion, traversal
*Circular linked list
*Doubly linked list
*Applications of linked lists (e.g., polynomial representation, memory management)

• Stacks and Linked Stack
*Applications:
*Expression evaluation (infix, postfix, prefix)
*Balancing symbols (parentheses matching)
*Function calls and recursion

• Queues
*Simple queue (array implementation)
*Circular queue
*Deque (double-ended queue)
*Priority queue
*Applications of queues (e.g., job scheduling, simulations)

• Trees
*Basic terminology (root, leaf, degree, height, etc.)
*Binary trees: representation and traversal (inorder, preorder, postorder)
*Binary search tree (BST): insertion, deletion, searching
*AVL trees, B-trees (introduction)
*Heap (min-heap, max-heap) and heap sort
*Applications of trees (expression trees, decision trees, Huffman coding)

• Graphs
*Graph terminology (vertices, edges, directed, undirected, weighted, unweighted)
*Representation: adjacency matrix, adjacency list
*Graph traversal: BFS (Breadth First Search), DFS (Depth First Search)
*Shortest path algorithms: Dijkstra’s, Floyd-Warshall
*Minimum spanning tree: Prim’s, Kruskal’s algorithms
*Applications of graphs (networks, social media, maps)

• Searching and Sorting
*Searching: Linear search, Binary search
*Sorting algorithms:
*Bubble sort, Insertion sort, Selection sort
*Merge sort, Quick sort, Heap sort
*Comparison of sorting techniques (time/space complexity)

• Hashing
*Hash functions and hash tables
*Collision resolution techniques: chaining, open addressing
*Applications of hashing (indexing, symbol tables)