To learn concept of data structures through abstract data structures including lists, stacks, queues, deques, sets, directed acyclic graphs, and graphs and implementations including the use of linked lists, arrays, binary search trees, hash tables, complete trees, and adjacency matrices and lists.
Upon successful completion of the course, the learner will be able to
Comprehend the given problem and predict the appropriate Data structure for solving them
Analyze the search complexity of the given Data structure with respect to time and space
Apply different Data structures to reduce the search complexity for the given set of Data by using optimized structures
Split and link the Data using linked list, to avoid continuous memory allocation for a huge set of Data
Implement the Stack data structure to implement the principle of Last In, First Out and apply in various real-time applications like browser history tracking(you hould have minimum 3 before you can use the term etc) etc.
Implement the Queue Data structure to implement the principle of First In First Out and apply in various real-time applications, like, process scheduling, etc.
Visualize the structure of the non-linear data structures like trees and graphs. Analyze the search complexity of the data arranged in non-linear structure
Reduce the search complexity further compared to non-linear Data structure by implementing the Hash Table Data structure
A Data structure is a specialized format for organizing and storing data in such a way that we can perform operations on these data in an effective way. In this module, you will have an introduction to Data structures by working out certain exercises on Strings, 1-D Arrays and 2-D Arrays.
A linked list is a Data structure which consists of a group of nodes (a node is a combination of data and link) that forms a sequence. In this module, you will learn how to use the linked list to store data. You will also learn about the various operations, like inserting, searching, updating and deleting data, that are performed on a Linked List. You will be able to visualize how these operations are performed by solving the analytical quiz questions that are given in this module.
In this module, you will learn how the operations such as reversing an linked list, ordering the linked list in ascending order, sorting the linked list and polynomial operations are done using the basic operations that was covered in the previous module.
A doubly linked list is a linked Data structure that consists of a set of sequentially linked records called nodes that contain two links, one is the next pointer and the other is the previous pointer. In this module, you will learn how to use the doubly linked list to store data. You will also learn about the various operations, like inserting, searching, updating and deleting data, that are performed on a Doubly Linked List.
Stack is a linear Data structure which follows the LIFO (Last In First Out) principle. In this module, you will learn how data is stored in a Stack using push method and how data is removed from the Stack using the pop function. You will also be learning how 1-D array and Linked List are used for the implementation of the Stack.
A queue is a linear Data structure which follows the FIFO (First In First Out) principle. In this module, you will learn how data is stored in a Queue using enqueue method and how data is removed from the Queue using the dequeue function. You will be learning how 1-D array and Linked List are used for the implementation of the Queue. You will also difference between the normal queue and the circular queue.
Tree is a non-linear Data structure that follows a hierarchical structure from root to leaf. In this module, you will learn how trees are used to store data systems, to increase the efficiency of the retrieval of data. You will also learn about the various operations, like inserting, searching, updating and deleting data, that are performed on a Complete Binary Tree.
The efficiency of searching can be increased for a tree only if some property is added to it. One such property is a Binary Search Tree (BST). In this module, you will learn about the implementation of the BST operations link insertion, traversal, searching and deletion. You will also understand how the search complexity has reduced significantly after building a BST.
A heap is a Complete Binary Tree that imposes a special property that holds the most prior element at its root. Heap is also called as Priority Queue. In this module, you will learn about the implementation of the Heap operations link insertion and deletion. You will also learn how sorting is performed using the Heap.
The more the structure becomes complex, the less will become the retrieval complexity. In this module, you will learn how the data is inserted and retrieved from a few advanced trees like, AVL Tree, B-Tree, Binomial Heap and Fibonacci Heap.
The set is a linear Data structure that stores unique values, without any particular order. In this module, you will learn about sets and the operations, like, Union and Find, performed on sets.
Hashing is the process of mapping the data to a key of normally smaller value and store it in a table, where, the table would be an array and the key is the index in the table. In this module, you will learn the various hashing techniques that are used to map the data to a key. You will also see the various techniques used to avoid the collision and the rehashing methods.
A graph is a non-linear Data structure that contains a set of points known as nodes (or vertices) that are connected by edges. In this module, you will learn about the matrix and linked list representation of the graph. You will be able to visualize the representations by solving the analytical quiz questions that are given in this module.
This module is a continuation of the Graphs module. In this module, you will learn about the two graph traversal methods, namely, Depth First Traversal and Breadth First Traversal.
In this module, you will learn how traversal methods are used to solve various graphs related problems. You will also learn about the other graph based algorithms like, Prims’s Algorithm, Kruskal’s Algorithm, Dijkstra's Algorithm, Floyd–Warshall's Algorithm and Bellman Ford's Algorithm.
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