Course Objectives

This course aims to:

• Introduce the fundamentals of Python programming language.
• Teach students to write clean, efficient, and readable Python code.
• Cover essential Python concepts like data types, control structures, functions, modules, and file handling.
• Explore object-oriented programming in Python.
• Introduce students to various Python libraries and their applications.

Course Outcomes

Upon completion of this course, students will be able to:

1. Write and execute Python programs using basic and advanced language features.
2. Apply object-oriented programming principles in Python.
3. Use Python libraries for various tasks like data manipulation, web development, and scientific computing.
4. Develop small-scale Python projects.

Detailed Syllabus

Module 1: Introduction to Python

• History and Features of Python
• Setting up Python Environment
• Basic Syntax and Data Types
• Variables, Operators, and Expressions
• Input and Output

Module 2: Control Flow and Functions

• Conditional Statements (if, elif, else)
• Loops (for, while)
• Functions: Defining and Calling Functions
• Function Arguments and Return Values
• Lambda Functions

Module 3: Data Structures

• Lists, Tuples, and Sets
• Dictionaries
• Strings and String Manipulation
• List Comprehensions

Module 4: Modules and File Handling

• Modules and Packages
• File Input and Output
• Working with CSV and JSON Files

Module 5: Object-Oriented Programming

• Classes and Objects
• Inheritance and Polymorphism
• Encapsulation and Abstraction

Module 6: Introduction to Libraries

• NumPy for Numerical Computing
• Pandas for Data Analysis
• Matplotlib for Data Visualization

Suggested Readings

• Python Crash Course by Eric Matthes
• Automate the Boring Stuff with Python by Al Sweigart
• Learning Python by Mark Lutz

List of Experiments

1. Programs based on basic Python constructs like variables, operators, and expressions.
2. Programs using conditional statements and loops.
3. Programs to manipulate lists, tuples, sets, and dictionaries.
4. Programs to perform file operations (reading and writing).
5. Programs to create and use classes and objects.
6. Programs demonstrating inheritance and polymorphism.
7. Programs using NumPy for numerical computations.
8. Programs using Pandas for data analysis and manipulation.
9. Programs using Matplotlib for data visualization.

Course Outcomes

Upon completion of this lab, students will be able to:

1. Write and execute Python programs using various language features.
2. Apply object-oriented programming concepts in Python.
3. Use Python libraries for data analysis and visualization.
4. Gain hands-on experience with file handling and data manipulation.