Advanced-Data Structures Lab’s detailed Cloud Computing & Big Data (CC) syllabus for the 2021 revision curriculum has been taken from the SITTTRs official website and presented for the Cloud Computing & Big Data (CC) students. For course code, course name, number of credits for a course and other scheme-related information visit the full semester subjects post below.
For the Cloud Computing & Big Data 5th Sem scheme and its subjects, visit the Cloud Computing & Big Data (CC) 5th Sem 2021 regulation scheme. For the Professional Elective-II scheme and its subjects, refer to the Cloud Computing & Big Data (CC) Professional Elective-II syllabus scheme. The detailed syllabus of the advanced data structures lab is as follows.
Course Objectives:
- Develop Python programs to perform advanced operations on graphs and trees.
- Implement Maps, Hash Tables and Set data structures in Python
- Develop Python programs for text-processing applications
Course Outcomes:
On completion of the course, students will be able to:
- Demonstrate graph algorithms for transitive closure, shortest path and minimum spanning tree
- Develop programs to perform operations on AVL trees
- Implement Maps, Hash Tables and Set data structures in Python
- Use text processing algorithms in Python
Module 1:
- Implement Floyd Warshall algorithm to find transitive closure of a directed graph using Python
- Demonstrate Dijkstra’s shortest path algorithm
- Apply the Prim-Jarnik Algorithm to find the Minimum Spanning Tree of a graph
- Find the Minimum Spanning Tree of a graph using Kruskal’s Algorithm.
Module 2:
- Develop a Python program to perform insert operations on AVL Trees.
- Implement delete operation on AVL Trees.
Module 3:
- Using maps, develop a Python program for counting word frequencies in a document
- Implement a Hash table with separate chaining for collision resolution
- Implement a Hash table with linear probing for collision resolution
- Develop Python programs to implement the set ADT and perform set operations.
Module 4:
- Implement pattern matching algorithm using the brute force approach
- Implement Huffman coding algorithm for text compression.
- Open-ended experiments
Text Books:
- Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, Data Structures and Algorithms in Python (An Indian Adaptation), Wiley; 1st edition (1 July 2021)
Reference Books:
- Bradley N Miller, Problem-Solving with Algorithms and Data Structures Using Python, Franklin Beedle & Assoc; Second edition (1 January 2013)
- Kent D. Lee, Steve Hubbard, Data Structures and Algorithms with Python, Springer, 2015
Online Resources
- https://www.edureka.co/blog/data-structures-in-python/
- https://realpython.com/python-data-structures/
- https://www.programiz.com/dsa
For detailed syllabus of all other Cloud Computing & Big Data subjects, 2021 revision curriculum, visit Cloud Computing & Big Data (CC) 5th Sem subject syllabuses for 2021 revision.
To see the syllabus of all other branches of the diploma 2021 revision curriculum, visit the SITTTR diploma all branches syllabus..
To see the results of Cloud Computing & Big Data of diploma 2021 revision curriculum, visit SITTTR diploma results..
For all Cloud Computing & Big Data academic calendars, visit the Cloud Computing & Big Data all semesters academic calendar direct link.