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Data Structures and Algorithms Using Python [1]

Paper Code: 
25CBDA211
Credits: 
03
Periods/week: 
03
Max. Marks: 
100.00
Objective: 

The course will enable the students to

1.   Develop  the  ability to choose between different available data structures.

2.   Develop  skills in students to implement algorithms on real  world problems and  evaluate their  performance

 

Course Outcomes: 

 

Course

Learning outcome

(at course level)

 

Learning and teaching strategies

 

Assessm ent Strategi es

 

Course

Code

 

Course

Title

 

 

 

 

 

 

 

 

 

 

25CBDA211

 

 

 

 

 

 

Data Structure s and Algorith ms using Python (Theory)

CO61. Critically  analyse  the   role of  algorithms  and   the   choice   of data  structures and   their   impact on the  performance of programs. CO62.    Examine      array      data structure  and   its   applications   in real  world  problems.

CO63.  Implement   link  list  data

structures, its  types and   analyse their  applications.

CO64.  Evaluate   applications   of stack  and  queue data structures. CO65. Recognize  the  use  of non- linear   data  structures in  real   life applications.

CO66.   Contribute  effectively  in course-specific interaction

Approach in te aching: Interact ive

Lectures, Discus sion,  Reading assignments,De monstration.

 

Learning activities for

the students: Se lf

learning assignme nts,

Effective  question s, Seminar presentation.

Class test, Semester end examinati ons,  Quiz, Practical Assignme nts, Presentati on.

 

9.00
Unit I: 
Introduction to Algorithms and Data Structure

Algorithm  definition and  its  characteristics, comparing algorithms, Abstract data types, Algorithm   analysis  and   its   types,  Asymptotic Notation:  Omega-n  Notation,  Theta-0Notation, Big O notation.Introduction to  Data  Structure: Data  Organisation. Types  of Data  structures: linear  and nonlinearObject oriented programming concepts

 

9.00
Unit II: 
Arrays

Arrays    (one,  two    and    multi-dimensional),.Array  operations   -   slicing,    dicing,    searching, matrix   operations,  searching  (linear   search,  binary   search)  and   sorting  arrays  (Exchange Sorts  (Bubble  sort,  Quick sort), Straight Selection sort,  and  Insertion sort.).

 

9.00
Unit III: 
Linked list

Introduction to  linked  list,  linked  list  as  a  data  structure,  creation, insertion and   deletion  of nodes  from   a  list,  comparing  linked   lists   with   arrays.  Doubly   Linked   lists,   Circular   linked lists .Application  of linked lists.

 

9.00
Unit IV: 
Stack

Definition,  Primitive   operations,  representing  stack   in  Python,  implementing  the   push  and pop  operation,  infix,   postfix    and    prefix    expression   (definition  and    examples),   infix   to postfix, evaluation  of  postfix   expression,  Applications. Recursion concepts  and   applications. Queues: Introduction,  Definition   of  Queue  and   its  sequential  representation,  python implementation of queues, insert and  remove operation,  Applications and  Priority queues

9.00
Unit V: 
Graphs and Trees

Terminology   &  Representations,  Graphs  &  Multi-graphs,   Directed   Graphs,  Elementary Graph   algorithms,   Representation  of  Graphs  ,Traversals:  BFS,  DFS.  Trees-Binary   tree, Terminology & Representation, Traversal of binary  trees, Binary Search Trees (BST).

ESSENTIAL READINGS: 

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

 

REFERENCES: 

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,2017

e-RESOURCES:

1.   Programming, Data  Structures And Algorithms  Using Python, Prof. MadhavanMukund,swayamcourse: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]

 

Academic Year: 
2025-26 [5]

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Source URL: https://csit.iisuniv.ac.in/courses/subjects/data-structures-and-algorithms-using-python

Links:
[1] https://csit.iisuniv.ac.in/courses/subjects/data-structures-and-algorithms-using-python
[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://csit.iisuniv.ac.in/academic-year/2025-26