Python Tutorial

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.

Basic Code Example

The following is a simple program that displays the message “Hello, World!” on the screen.

print("Hello World!")

Hello World!

Why Learn Python?

• Requires fewer lines of code compared to other programming languages like Java.
• Provides libraries and frameworks such as Django and Flask for web development and tools like Pandas, TensorFlow and Scikit-learn for artificial intelligence, machine learning and data analysis.
• Cross-platform, works on Windows, Mac and Linux without major changes.
• Used by top tech companies like Google, Netflix and NASA.
• Many Python coding job opportunities in Software Development, Data Science and AI/ML.

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: Hangman Game

Functions

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

• Functions
• Pass in Functions
• Global and Local Variables
• Recursion
• *args and **kwargs in Function
• First Class Function
• Lambda Function
• Map, Reduce and Filter Function
• Inner Function
• Decorators
• Project: 21 Number game

Data Structures

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

• Strings
• List
• Tuples
• Dictionary
• Sets
• Arrays
• List Comprehension
• Project: 2048 Game

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

• Counters
• Heapq
• Deque
• OrderedDict
• Defaultdict
• Complete Tutorial on DSA with Python

OOP Concepts

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

• Python OOP
• Classes and Objects
• Constructors
• ‘Self’ as Default Argument
• Polymorphism
• Inheritance
• Abstraction
• Encapsulation
• Iterators
• Project: Banking System

Exception Handling

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

• Exception Handling
• Built-in Exception
• User defined Exception

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

Database Handling

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

• MongoDB Introduction
• MySQL Introduction
• Project: Management System

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
• Complete Tutorial on Data Science
• Project: Sentiment Analysis

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)
• Complete Tutorial on Web Development
• Project: ToDo webapp

Chapter-wise Practice Quiz

Quiz helps learners test their understanding of Python concepts through short, practice important topics and improve problem-solving skills.

• Python Fundamentals: Basics, Input and Output, Data Types, Numbers, Boolean.
• Control Flow & Functions: Control Flow, Loops, Functions.
• Data Structures: String, List,  Tuples, Dictionary, Sets, Arrays, List Comprehension.
• Collections Module: Counters, Heapq, Deque, OrderedDict.
• Object-Oriented Programming: OOP Concepts.
• Exception & File Handling: Exception Handling, File Handling.

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.