JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Pre-Requisites

UG level course in Data Structures

Course Objectives

This course will enable students to

• 1. Implement Object Oriented Programming concepts in Python.
• 2. Understand Lists, Dictionaries and Regular expressions in Python.
• 3. Understanding how searching and sorting is performed in Python.
• 4. Understanding how linear and non-linear data structures works.
• 5. To learn the fundamentals of writing Python scripts.

Course Outcomes

The students should be able to:

• 1. Examine Python syntax and semantics and apply Python flow control and functions.
• 2. Create, run and manipulate Python Programs using core data structures like Lists,
• 3. Apply Dictionaries and use Regular Expressions.
• 4. Interpret the concepts of Object-Oriented Programming as used in Python.
• 5. Master object-oriented programming to create an entire python project using objects and classes

UNIT - I

Oops Concepts- class, object, constructors, types of variables, types of methods. Inheritance: single, multiple, multi-level, hierarchical, hybrid, Polymorphism: with functions and objects, with class methods, with inheritance, Abstraction: abstract classes.

UNIT - II

Data Structures – Definition, Linear Data Structures, Non-Linear Data Structures Python Specific Data Structures: List, Tuples, Set, Dictionaries, Comprehensions and its Types, Strings, slicing.

UNIT - III

Arrays - Overview, Types of Arrays, Operations on Arrays, Arrays vs List. Searching -Linear Search and Binary Search. Sorting - Bubble Sort, Selection Sort, Insertion Sort, Merge Sort, Quick Sort.

UNIT - IV

Linked Lists – Implementation of Singly Linked Lists, Doubly Linked Lists, Circular Linked Lists. Stacks - Overview of Stack, Implementation of Stack (List & Linked list), Applications of Stack Queues: Overview of Queue, Implementation of Queue (List & Linked list), Applications of Queues, Priority Queues.

UNIT - V

Graphs -Introduction, Directed vs Undirected Graphs, Weighted vs Unweighted Graphs, Representations, Breadth First Search, Depth First Search. Trees - Overview of Trees, Tree Terminology, Binary Trees: Introduction, Implementation, Applications. Tree Traversals, Binary Search Trees: Introduction, Implementation, AVL Trees: Introduction, Rotations, Implementation.

TEXT BOOKS:

• 1. Data structures and algorithms in python by Michael T. Goodrich
• 2. Data Structures and Algorithmic Thinking with Python by Narasimha Karumanchi

REFERENCE BOOKS:

• 1. Hands-On Data Structures and Algorithms with Python: Write complex and powerful code using the latest features of Python 3.7, 2nd Edition by Dr. Basant Agarwal, Benjamin Baka.
• 2. Data Structures and Algorithms with Python by Kent D. Lee and Steve Hubbard.
• 3. Problem Solving with Algorithms and Data Structures Using Python by Bradley N Miller and David L.Ranum.
• 4. Core Python Programming -Second Edition,R. Nageswara Rao, Dreamtech Press.