Python is one of the most popular programming languages. It’s simple to use, packed with features and supported by a wide range of libraries and frameworks. Its clean syntax makes it beginner-friendly.

• A high-level language used in data science, automation, AI, web development and more.
• Known for its readability, which means code is easier to write, understand and maintain.
• Backed by strong library support, we don’t have to build everything from scratch.

The following is a classic program that displays “Hello, World!”. This program is explained in detail in Python Introduction.

print("Hello World!")

Basics

Start with Python fundamentals, including installation and concepts needed to start programming with Python.

• Introduction
• Applications
• Input and Output
• Variables & Operators
• Keywords & Data Types
• Conditional Statements & Loops
• Project: Rock Paper Scissor Game
• Quiz: Basics, I/O, Data Types, Control Flow, Loops
• Exercise: Printing, Decision Making, Multiplication Table

Functions

Learn how to organize code into reusable blocks for performing specific tasks.

• Functions & Pass
• Global and Local Variables
• Recursion
• *args and **kwargs in Function
• First Class & Lambda Function
• Map, Reduce and Filter Function
• Inner Function & Decorators
• Project: Number Guessing Game
• Quiz: Functions
• Exercise: Return Value, No Arguments

Data Structures

Learn how to store, organize and work with different types of data.

• Strings
• List & Tuples
• Dictionary & Sets
• Arrays & List Comprehension
• Project: Tic Tac Toe Game
• Quiz: String, List,  Tuples, Dictionary, Sets, List Comprehension
• Exercise: Reverse String, List Sum, First Repeating

Python's collections module offers essential data structures, including the following:

• Counters
• Heapq & Deque
• OrderedDict & Defaultdict
• Quiz: Counters, Heapq, Deque, OrderedDict
• Exercise: Height of Heap, Maximum Diamonds, Rotten Oranges
• Complete Tutorial: DSA with Python

OOP Concepts

Learn how to use object-oriented programming to organize code using classes and objects.

• Classes and Objects
• Constructors
• ‘Self’ as Default Argument
• Polymorphism
• Inheritance
• Abstraction
• Encapsulation
• Iterators
• Project: Banking System
• Quiz: OOP Concepts
• Exercise: Design a class, Encapsulation, Abstraction

Exception Handling

Learn how to handle errors and prevent programs from stopping unexpectedly.

• Exception Handling
• Built-in Exception
• User defined Exception
• Exercise: Exception Practice
• Quiz: Exception Handling

File Handling

Learn how to create, read, write and manage files in Python.

• File Handling
• Read Files
• Write/Create Files
• OS Module
• pathlib Module
• Directory Management
• Quiz: File Handling

Database Handling

Learn how to connect Python applications with databases and work with stored data.

• MongoDB Introduction
• MySQL Introduction
• Project: Management System
• Quiz: MySQL, MongoDB
• Exercise: SQL

Packages or Libraries

Explore Python packages and libraries that provide ready-to-use tools for different tasks.

Some commonly used types of libraries include:

• Packages
• Built-in Modules
• DSA Libraries
• GUI Libraries
• Project: Screen Recorder

Data Science

1. Foundational Libraries: These are the libraries that form the base for all data science work. Start here to build a strong foundation.

• NumPy
• Pandas
• Matplotlib

2. Advanced Visualization and Statistical Tools: Once you’re comfortable with basic data handling and visualization, move to creating cleaner visuals and performing statistical analysis.

• Seaborn
• Statsmodel

3. Machine Learning Libraries: After data manipulation and visualization, learn machine learning, starting with simpler models and moving to advanced ones.

• Scikit-learn
• XGBoost /LightGBM

4. Deep Learning Frameworks: If you’re interested in AI and deep learning, these libraries will allow you to build and train neural networks.

• TensorFlow and Keras
• PyTorch
• Project: Sentiment Analysis
• Complete Tutorial: Data Science

Web Development

1. Core Web Frameworks (Backend Development with Python): These are the tools for building Python-based web applications.

• Flask
• Django

2. Database Integration: Learn how to connect Python web frameworks to databases for storing and retrieving data.

• SQLite
• SQLAlchemy
• MySQL

3. Front-End and Backend Integration: Learn how to connect Python backends with front-end technologies to create dynamic, full-stack web applications.

• Jinja2 (Flask)
• Django Templates

4. API Development: Learn to build APIs (Application Programming Interfaces) for connecting your backend with front-end apps or other services.

• Flask-RESTful
• Django REST Framework (DRF)
• Project: ToDo webapp
• Complete Tutorial: Web Development

Interview Questions and Practice Problems

This section provides a collection of commonly asked Python interview questions and practice problems to help you prepare for technical interviews and improve your coding skills.

• Interview Questions and Answers
• Coding Problems

This Python tutorial is updated based on latest Python 3.13.13 version.