Importance of Data Structure
A data structure is a way of organizing and storing data to perform operations efficiently, such as searching, sorting, and modifying data. Data structures provide the foundation for designing efficient algorithms to solve computational problems. Using the right data structure minimizes memory usage and enhances CPU efficiency.
Data Structure
- Category: Programming
- Project: One Academic Project
- Duration: 2 Month
Syllabus
Introduction to Data Structure
- Basics of data structures and algorithms
- Complexity analysis (time and space)
- Role of C++ in data structures
Arrays and Strings
- 1D and 2D arrays
- Operations (insertion, deletion, searching, sorting)
- Strings and string manipulation
Recursion
- Basics and types of recursion
- Recursive algorithms (e.g., factorial, Fibonacci, tower of Hanoi)
Searching and Sorting Algorithms
Searching Algorithms
- Linear search and binary search
- Interpolation and exponential search
Sorting Algorithms
- Bubble, selection, and insertion sort
- Merge sort, quicksort, and heap sort
- Time complexity comparison
Linked Lists
- Singly linked list (creation, insertion, deletion, traversal)
- Doubly and circular linked lists
- Applications of linked lists
Stacks
- Stack implementation using arrays and linked lists
- Push, pop, and peek operations
- Applications (e.g., parentheses matching, postfix evaluation)
Queues
- Types: simple, circular, and priority queues
- Implementation using arrays and linked lists
- Applications (e.g., task scheduling)
Trees
- Binary trees (traversals: in-order, pre-order, post-order)
- Binary search tree (BST)
- AVL tree and tree balancing
- B and B+ Tree
- M-Way Tree
Heaps
- Introduction to heaps (min-heap and max-heap)
- Heap operations and applications
- Priority queues using heaps
Graphs
- Representation (adjacency matrix and list)
- Graph traversal algorithms (BFS, DFS)
- Applications of graphs (e.g., shortest path, MST)
Hashing
- Hash tables and hash functions
- Collision handling (chaining, open addressing)
- Applications of hashing
Dynamic Programming
- Basic concepts and problems (e.g., knapsack, LCS, Fibonacci)
- Optimization using memoization and tabulation
Advanced Data Structures (Optional)
- Trie, segment tree, and Fenwick tree
- Disjoint set union (Union-Find)