Python Tutorial - Learn Python Programming Language
Last Updated :
11 Aug, 2025
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. It's
- A high-level language, used in web development, data science, automation, AI and more.
- Known for its readability, which means code is easier to write, understand and maintain.
- Backed by library support, so we don’t have to build everything from scratch, there’s probably a library that already does what we need.
Why to Learn Python?
- Requires fewer lines of code compared to other programming languages.
- Provides Libraries / Frameworks like Django, Flask, Pandas, Tensorflow, Scikit-learn and many more for Web Development, AI/ML, Data Science 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.
Do you wish to learn Python in a scheduled manner ? Try our ongoing free course Python Skillup with weekly topic coverage, notes, daily quizzes and coding problems.
First Python Program
Here is a simple Python code, printing a string. We recommend you to edit the code and try to print your own name.
Python
1. Python Basics
In this section, we’ll cover the basics of Python programming, including installing Python, writing first program, understanding comments and working with variables, keywords and operators.
Before starting to learn python we need to install python on our system.
2. Python Functions
In this section of Python 3 tutorial we'll explore Python function syntax, parameter handling, return values and variable scope. Along the way, we'll also introduce versatile functions like range(), map, filter and lambda functions.
3. Python Data Structures
Python offers versatile collections of data types, including lists, string, tuples, sets, dictionaries and arrays. In this section, we will learn about each data types in detail.
Python's collections module offers essential data structures, including the following:
To learn data structure and algorithm with python in detail, you can refer to our DSA with Python Tutorial.
4. Python OOP Concepts
In this section, we'll explore the core principles of object-oriented programming (OOP) in Python. From encapsulation to inheritance, polymorphism, abstract classes and iterators, we'll cover the essential concepts that helps you to build modular, reusable and scalable code.
5. Python Exception Handling
In this section, we'll explore Python Exception Handling that how Python deals with unexpected errors, enabling us to write fault-tolerant code. We'll cover file handling, including reading from and writing to files.
6. File Handling
In this section, we will cover file handling, including reading from and writing to files.
7. Python Database Handling
In this section we will learn how to access and work with MySQL and MongoDB databases
8. Python Packages or Libraries
Python is a huge collection of Python Packages standard libraries that make development easier. These libraries help with a wide range of tasks and can save you a lot of time by providing ready-to-use tools.
Some commonly used types of libraries in Python include:
9. Data Science with Python
1. Foundational Libraries: These are the libraries that form the base for all data science work. Start here to build a strong foundation.
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.
3. Machine Learning Libraries: After data manipulation and visualization, learn machine learning, starting with simpler models and moving to advanced ones.
4. Deep Learning Frameworks: If you’re interested in AI and deep learning, these libraries will allow you to build and train neural networks.
To learn more, you can refer to Python for Data Science.
10. Web Development with Python
1. Core Web Frameworks (Backend Development with Python): These are the tools for building Python-based web applications.
2. Database Integration: Learn how to connect Python web frameworks to databases for storing and retrieving data.
3. Front-End and Backend Integration: Learn how to connect Python backends with front-end technologies to create dynamic, full-stack web applications.
4. API Development: Learn to build APIs (Application Programming Interfaces) for connecting your backend with front-end apps or other services.
To learn more, you can refer to Python for Web Development.
Applications of Python
- Web Development: Frameworks like Django and Flask can be used to create dynamic websites and web applications quickly and efficiently.
- Data Science & Analysis: Python is most preferred language for data analysis, visualization and handling large datasets. Because of extensive libraries like Pandas, NumPy and Matplotlib.
- Machine Learning & AI: Python is popular in AI and machine learning because of its powerful libraries like TensorFlow, Keras and Scikit-learn.
- Scripting & Automation: Python’s simplicity makes it ideal for writing scripts that automate tasks in different systems, from server management to file handling. Python is commonly used to automate repetitive tasks, making processes faster and more efficient.
- Web Scraping: Libraries like Beautiful Soup and Scrapy.
- Desktop App Development: Python can be used to build desktop applications using frameworks like Tkinter and PyQt. Python is also used for game development, with libraries like Pygame to create simple games.
Python Practice
Python quiz page covers topics including variables, data types, input, output, lists, tuples, dictionaries and sets. The Python Coding Practice Problems page offers exercises on loops, functions, lists, strings, dictionaries, sets and advanced structures like heaps and deques.
This Python tutorial is updated based on latest Python 3.13.1 version.
Important Links
Python Introduction
How Python Programs are Executed
Comments in Python
Variables in Python
List Introduction
Set in Python
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