Python Programming Language
•An Introduction to Python – Simple, Powerful, and Popular.
Used worldwide for Web Development, Data Science, Artificial
Intelligence, Automation, and more.
2.
History of Python
•• Created by Guido van Rossum in 1991.
• Named after the British comedy group 'Monty Python'.
• Open-source and community-driven.
• Python 2 vs Python 3 – Python 3 is the present and future.
3.
Features of Python
•• Easy to learn and use with simple syntax.
• Interpreted and dynamically typed.
• Object-oriented and functional programming support.
• Huge standard library.
• Cross-platform and portable.
4.
Why Learn Python?
•• Most popular programming language globally.
• High demand in IT industry.
• Used in AI, ML, Web Apps, Data Analytics.
• Strong online community and support.
• Ideal for both beginners and experts.
Installing Python
• •Download from python.org.
• Works on Windows, Mac, Linux.
• Install IDEs like PyCharm, VS Code, Jupyter Notebook.
• Verify installation: python --version.
7.
First Program: HelloWorld
• print('Hello, World!')
Explanation:
• print() is a built-in function.
• Displays output on screen.
• First step to start coding in Python.
8.
Python Syntax Basics
•• Indentation is mandatory (no braces).
• Case-sensitive language.
• Variables don’t need explicit declaration.
• Comments use # symbol.
• Example:
for i in range(3):
print(i)
Variables & Constants
•• Python variables don’t need type declaration.
• Example: x=10, name='Ayush'.
• Constants are written in UPPERCASE by convention.
• Example: PI = 3.14.
Loops in Python
•• For loop – for i in range(5).
• While loop – while x < 10.
• Break and continue statements.
• Example:
for i in range(1,6):
print(i)
14.
Functions in Python
•• Defined using def keyword.
• Supports arguments and return values.
• Example:
def add(a,b):
return a+b
print(add(5,3))
15.
Modules & Packages
•• Built-in modules: math, os, datetime.
• External libraries via pip install.
• Example:
import math
print(math.sqrt(16))
Popular Python Libraries
•• NumPy & Pandas – Data Analysis.
• Matplotlib & Seaborn – Data Visualization.
• Django & Flask – Web Development.
• TensorFlow & PyTorch – AI/ML.
• OpenCV – Computer Vision.
20.
Conclusion
• • Pythonis versatile and beginner-friendly.
• Backbone of Data Science, AI, and Web Apps.
• Large supportive community.
• Great career opportunities.
Keep Practicing Python Daily!
👉