Data Structures and Algorithms detailed syllabus for Cloud Computing & Big Data (CC) for 2021 revision curriculum has been taken from the SITTTRs official website and presented for the Cloud Computing & Big Data students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Cloud Computing & Big Data 4th Sem scheme and its subjects, do visit Cloud Computing & Big Data (CC) 4th Sem 2021 revision scheme. The detailed syllabus of data structures and algorithms is as follows.
Course Objectives:
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Course Outcomes:
On completion of the course, the student will be able to:
- Illustrate the basic data structure concepts through python language
- Use different Searching and Sorting Algorithms
- Demonstrate linear data structures Stack, Queue and Linked Lists
- Sketch nonlinear Data Structures such as Tree and graph
Module 1:
Algorithms: Definition, Asymptotic Analysis of Algorithms- The “Big-Oh” Notation, Big Omega Notation, Recursion Data Structures: Definition, Classification- Linear Data Structures, Non-Linear Data Structures, Abstract Data Type(ADT) Arrays: Array based sequences,operations-Traverse,insert,delete,search,update -Two Dimensional Arrays in python
Module 2:
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Module 3:
Stacks: Introduction to Stack ADT – Array Representation of Stacks – Operations on a Stack – Applications of Stacks – Infix-to-Postfix Conversion – Evaluating Postfix Expressions. Queues: Introduction to Queue ADT – Array Representation of Queues – Operations on a Queue – Types of Queues: Circular Queue – Dequeue. Linked Lists: Singly Linked List – Representation in Memory, Operations on a Singly Linked List – Insertion, Deletion, Searching and Traversal. Types of Linked List- Circularly Linked Lists, Doubly Linked Lists. Linked List Representation of Stack and Queue
Module 4:
Graphs: Graph Terminologies – Vertex, Edge, Adjacent vertices, Self-loop, Parallel edges, Isolated vertex, Degree of vertex, Pendant vertex, Subgraph, Paths and Cycles. Types of Graphs – Directed, Undirected, Simple, Complete, Cyclic, Acyclic, Bipartite, Complete Bipartite, Connected, Disconnected and Regular. Representation of Graphs – Set – Linked – Matrix Graph Traversals-BFS, DFS Trees: Definition – Basic Terminologies – Node, Parent, Child, Link, Root, Leaf, Level, Height of a tree and node, Depth of a tree and node, Degree of a tree and node, sibling, Ancestors, Path, Path Length. Binary Tree- Types of Binary Trees: Full, Complete, Strict, Perfect. Representations of a Binary Tree using Linked Lists Tree Traversal Algorithms- Inorder, Preorder, Postorder. Operations on a Binary Search Tree: Insertion -Traversal – Deletion- Count number of nodes – Height of a BST
Text Books:
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Reference Books:
- Bradley N Miller Problem Solving with Algorithms and Data Structures Using Python, Franklin Beedle & Assoc; Second edition (1 January 2013)
Online Resources
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
For detailed syllabus of all other subjects of Cloud Computing & Big Data (CC), 2021 revision curriculum do visit Cloud Computing & Big Data 4th Sem subject syllabuses for 2021 revision.
To see the syllabus of all other branches of diploma 2021 revision curriculum do visit SITTTR diploma all branches syllabus..
To see the results of Cloud Computing & Big Data (CC) of diploma 2021 revision curriculum do visit SITTTR diploma Cloud Computing & Big Data (CC) results..
For all Cloud Computing & Big Data academic calendars, visit Cloud Computing & Big Data all semesters academic calendar direct link.