Course: Data Structures And Analysis Of Algorithms:
Time COmplexity, Space Complexity, Linked List, Stacks, Queues, Trees, AVL Trees, Hash Tables, Graphs, Spanning Trees, Prim's Algorithm, Kruskal's Algorithm, Searching and Sorting Techniques, Dynamic Programming, Divide and Conquer, Greedy Algorithms, Interview Questions, Campus Placements, Live Projects
Objectives:
- Basic concepts such as Abstract Data Types, Linear and Non Linear Data structures.
- Analyze the performance and analysis of algorithms (Time Complexity and Space Complexity, Big O notation).
- Greedy Algorithms, Divide and Conquer, Dynamic Programming.
- Behavior of data structures such as Linked List (Doubly Linked List), stacks, queues, circular queues, trees (BST, AVL), search trees, priority queues, hash tables.
- Graphs and their representations, Spanning Tree, Minimum Spanning Tree (MST).
- Prim's Algorithm, Kruskal's Algorithm, Shortest Path using Dijkstra's Algorithm.
- Choose the appropriate data structure for a specified application.
- Analysis and implementation of various searching (Linear Search, Binary Search, Interpolation Search) algortihms
- Analysis and implementation of various sorting (Bubble Sort, Insertion Sort, Quick Sort, Selection Sort, Merge Sort, Shell Sort, Quick Sort, Heap Sort) algorithms.
- Write programs in C/C++/Java to solve problems using data structures such as
- arrays, linked lists, doubly linked list, stacks, queues, circular queues, trees, graphs, hash tables, search trees.
Duration: 30 hours Theory, 90 hours Practical (Recommended)
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