MSBTE K Scheme – 313306 Data Structure Using Python
MSBTE K Scheme – Data
Structure Using Python Notes PDF
The subject “Data
Structure Using Python” under the MSBTE K Scheme for Computer
Engineering diploma is one of the most important subjects that builds a
student’s problem-solving, logical thinking, and programming foundation.
A data
structure is simply a way of organizing and storing data so that it can be
used efficiently. Python, being a modern and powerful programming language,
makes it easier to implement various data structures like stacks, queues,
linked lists, trees, and graphs with less code and better readability.
This subject
helps students to think like computer scientists, understand how data
is managed in memory, and apply it to solve real-life problems.
Why Learn Data Structure Using Python?
- Python Advantage – Python provides built-in
libraries and simple syntax to implement data structures.
- Efficiency – Choosing the right data
structure improves program speed and memory usage.
- Problem Solving – Data structures form the
backbone of algorithms, AI, machine learning, and databases.
- Industry Relevance – Every software engineer
must know data structures for coding interviews and real-world projects.
MSBTE K Scheme Syllabus Overview – Data Structure
Using Python
The syllabus covers both theory
concepts and practical implementation of data structures in Python.
Unit 1: Introduction to Data
Structures
- Definition, need, and importance of data structures
- Types: Primitive (int, float, char) and
Non-Primitive (arrays, linked lists, stacks, queues, trees, graphs)
- Applications of data structures in real life
Unit 2: Arrays and Strings
- Concept of arrays in Python (using lists)
- Operations: Traversing, inserting, deleting,
searching, sorting
- String operations: concatenation, substring,
reversal, palindrome check
Unit 3: Stack and Queue
- Stack: LIFO (Last In First Out) principle
- Implementation using list and collections.deque in
Python
- Applications of stack: expression evaluation,
undo-redo operations
- Queue: FIFO (First In First Out) principle
- Types of queues: Simple queue, circular queue,
priority queue, double-ended queue
- Implementation in Python using deque and queue
module
Unit 4: Linked List
- Concept of nodes and pointers in Python
- Types of linked lists: singly, doubly, circular
- Operations: insertion, deletion, traversal
- Advantages of linked list over arrays
Unit 5: Trees and Graphs
- Tree basics: root, node, leaf, parent-child
relationships
- Binary tree and Binary Search Tree (BST)
- Tree traversal techniques: inorder, preorder,
postorder
- Graph representation: adjacency matrix and
adjacency list
- Graph traversal: BFS (Breadth First Search) and DFS
(Depth First Search)
Unit 6: Searching and Sorting Techniques
- Searching: Linear search, Binary search
- Sorting: Bubble sort, Insertion sort, Selection
sort, Merge sort, Quick sort
- Practical implementation in Python
Practical Work in MSBTE Data Structure Using Python
Students will perform practical
assignments to strengthen concepts:
- Python programs for array insertion, deletion, and
searching
- Implementing stack using list and testing push/pop
operations
- Queue implementation using collections.deque
- Linked list creation with insert and delete
operations
- Binary tree construction and traversal
- Graph traversal using BFS and DFS
- Implementation of sorting algorithms (bubble,
selection, quick, merge)
Importance of This Subject
- Exams – Direct questions on array
operations, stack/queue implementations, and sorting algorithms.
- Coding Interviews – Data structures are
always asked in IT/software placements.
- Projects – Helps in real-life applications
like databases, compilers, social networks, search engines.
- Higher Studies – Foundation for advanced
topics like machine learning, AI, cloud computing, big data.
Real-Life Applications of Data Structures
- Stack → Undo/redo in text editors, browser
back button
- Queue → Ticket booking systems, printer
queue
- Linked List → Music playlist navigation,
dynamic memory allocation
- Tree → File systems in operating systems
- Graph → Social networks like Facebook,
Google Maps navigation
- Sorting & Searching → E-commerce search
results, ranking systems
Study Tips for MSBTE Students
- Focus on concept + Python implementation
(write and run code yourself).
- Practice diagram-based questions (stack,
queue, linked list, trees).
- Remember time complexity (Big O notation) of
algorithms.
- Solve previous years’ MSBTE question papers.
- Revise differences between data structures
(stack vs queue, array vs linked list).
Career Scope
After mastering Data Structure
Using Python, students can pursue roles such as:
- Python Developer
- Software Engineer
- Data Analyst
- Machine Learning Engineer
- Algorithm Developer
- Competitive Programmer
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