The objective of course is to:
1. Implement the different data structures using python programming language.
2. Develop real world applications using object oriented programming in python
Course | Learning outcome (at course level) | Learning and teaching strategies | Assessment Strategies | |
Course Code | Course Title | |||
25CBDA 212 |
Data Structures and Algorithms Lab (Practical) | CO67. Write programs to implement different operations on arrays and matrices; and arrange data using different sorting techniques. CO68. Design the different linked lists and get practical knowledge on its application. CO69. Implement queue and stack using python. CO70. Write programs to implement graphs and trees. CO71. Apply object oriented programming concepts in python. CO72. Contribute effectively in course-specific interaction | Approach in teaching: Interactive Lectures, Group Discussion, Case Study, Demonstration
Learning activities for the students: Self-learning assignments, Exercises related with Machine Learning algorithm, presentations | Class test, Semester end examinations, Quiz, Practical Assignments, Presentation |
Contents: Exercises based on the following topics:
● 1-D and n-D Arrays
● Sorting & searching
● Stacks
● Queues
● Linked-Lists-Single, Doubly Linked Lists and Circular Linked Lists
● Graphs
● Trees -Binary Trees, Binary Search Trees and Traversals
● Concepts of Object oriented programming in python
1. Tamassia, Roberto., Goodrich, Michael T.., Goldwasser, Michael H. Data Structures andAlgorithms in Python. United States: John Wiley & Sons, Incorporated, Latest Ed.
2. Nagarajan, Abhishek S.., Vasudevan, Shriram K.., Nanmaran, Karthick. Data StructuresUsing Python. India: Oxford University Press, 2020.
3.Goodrich, Michael T., Roberto Tamassia, and Michael H. Goldwasser. Data Structures and Algorithms in Python: An Indian Adaptation. Wiley Publications, 2021
4.McKinney, Python for Data Analysis. O’ Reilly Publication,2017.
SUGGESTED READINGS:
1. Miller, Curtis. Hands-On Data Analysis with NumPy and Pandas: Implement Python Packages from Data Manipulation to Processing. United Kingdom: Packt Publishing, 2018.
2. Jean-Paul Tremblay, Paul G. Sorenson, “An Introduction To Data Structures With Application”, McGraw Hill Education, Latest Edition.
e-RESOURCES:
1. Programming, Data Structures And Algorithms Using Python, Prof. Madhavan Mukund , swayam course: https://onlinecourses.nptel.ac.in/noc23_cs95/preview
2. https://www.tutorialspoint.com/python_data_structure/index.htm [2]
3. https://www.geeksforgeeks.org/python-data-structures-and-algorithms/ [3]
4. https://jovian.ai/learn/data-structures-and-algorithms-in-python
JOURNALS:
1. Journal of Machine Learning Research (JMLR),ACM, https://dl.acm.org/journal/jmlr
2. International Journal of Machine Learning and Cybernetics, springer :https://www.springer.com/journal/13042 [4]
Links:
[1] https://www.csit.iisuniv.ac.in/courses/subjects/data-structures-and-algorithms-lab-2
[2] http://www.tutorialspoint.com/python_data_structure/index.htm
[3] http://www.geeksforgeeks.org/python-data-structures-and-algorithms/
[4] http://www.springer.com/journal/13042
[5] https://www.csit.iisuniv.ac.in/academic-year/2025-26