The Best free resources to learn python from scratch

Introduction: Why Python and Why Free Resources?

Python has emerged as one of the most popular programming languages worldwide, and for good reason. With its clean syntax, versatility, and extensive library ecosystem, Python serves as an excellent gateway into the world of programming. Whether you’re interested in web development, data science, artificial intelligence, automation, or simply want to enhance your problem-solving skills, Python provides the foundation.

The beauty of learning Python today is the abundance of high-quality, completely free resources available. Gone are the days when learning to code required expensive courses or degree programs. The open-source community and educational institutions have created an incredible wealth of materials that can take you from absolute beginner to proficient programmer without spending a dime.

This comprehensive guide will walk you through the best free resources available, organized to support your learning journey from day one through intermediate levels and beyond. We’ll cover interactive platforms, video courses, textbooks, practice environments, community resources, and specialized learning paths.

Phase 1: Absolute Beginner Resources (First 2-4 Weeks)

Interactive Learning Platforms

1. Codecademy’s Free Python Course

What it offers: An interactive, browser-based environment where you write real Python code from your first lesson. The free version covers Python fundamentals including syntax, functions, control flow, lists, loops, and dictionaries.
Why it’s great for beginners: Immediate feedback, hands-on practice, and gradual complexity increase make this ideal for those who learn by doing.
Limitations: The free version covers basics but not advanced topics. Premium features require payment.
Time commitment: 20-25 hours to complete the free track.

2. freeCodeCamp’s Scientific Computing with Python

What it offers: A project-based curriculum that teaches Python through building actual applications. The course includes over 300 hours of content and culminates in five certification projects.
Why it’s great for beginners: Completely free with no paywalls, project-based learning reinforces concepts, and the certification provides tangible proof of skills.
Structure: Starts with basic concepts and progresses through string manipulation, file I/O, regular expressions, and basic algorithms.
Certification: Upon completion, you earn a free certification that can be added to your LinkedIn profile or resume.

3. Python Principles

What it offers: A minimalist platform that teaches Python through short lessons and immediate practice exercises. The site’s philosophy is “learn by doing” with an emphasis on writing code from the very beginning.
Unique features: Challenges get progressively harder, and the clean interface minimizes distractions.
Best for: Learners who prefer straightforward, no-frills instruction.

4. Google’s Python Class

What it offers: Originally created for Google employees with some programming experience, this resource has been adapted for complete beginners. It includes written materials, lecture videos, and coding exercises.
Content: Covers strings, lists, sorting, dicts, files, and regular expressions.
Format: Primarily text-based with supporting videos, making it excellent for those who prefer reading to watching.
Prerequisites: Some programming experience is helpful but not required.

Video-Based Learning

1. CS50’s Introduction to Programming with Python (Harvard University)

What it offers: Harvard’s famous CS50 course adapted specifically for Python. Professor David Malan’s engaging teaching style makes complex concepts accessible.
Content: Covers functions, variables, conditionals, loops, exceptions, libraries, unit tests, file I/O, regular expressions, and object-oriented programming.
Format: Lecture videos, problem sets, and a supportive online community.
Certification: Free certificate of completion (with optional paid verified certificate).
Time commitment: 10-20 hours per week for 9 weeks.

2. Programming with Mosh (YouTube)

What it offers: Mosh Hamedani’s “Python Tutorial for Beginners” is one of the most-watched Python courses on YouTube, with over 30 million views.
Content: 6-hour comprehensive video covering installation, variables, types, control flow, functions, data structures, exceptions, classes, modules, and standard libraries.
Teaching style: Clear, concise explanations with practical examples.
Best for: Visual learners who prefer video instruction.

3. Corey Schafer’s Python Tutorial Series (YouTube)

What it offers: Extremely well-produced tutorials covering Python fundamentals and intermediate topics in depth.
Content: Over 40 videos covering setup, basics, OOP, decorators, generators, modules, virtual environments, and popular libraries.
Unique value: Corey explains not just “how” but “why,” providing deeper understanding than typical tutorial videos.
Production quality: Professional editing and clear audio make for an excellent viewing experience.

4. freeCodeCamp’s Python Full Course for Beginners (YouTube)

What it offers: A 4.5-hour comprehensive video course covering all Python fundamentals with hands-on coding demonstrations.
Content: Variables, data types, strings, lists, tuples, sets, dictionaries, conditionals, loops, functions, classes, and modules.
Teaching style: The instructor codes along with viewers, making it easy to follow.
Supplemental materials: Links to code samples and additional resources.

Text-Based Resources

1. Python for Everybody (py4e.com)

What it offers: Dr. Charles Severance’s complete course materials including textbook, slides, lecture videos, and assignments. The associated book “Python for Everybody” is available for free online.
Content: Designed specifically for beginners with no programming background, focusing on data manipulation and basic programming concepts.
Structure: Each chapter includes text, video lectures, auto-graded assignments, and discussion forums.
Certifications: Free certificate available through Coursera (audit the course for free).
Accessibility: Available in multiple languages and formats (web, PDF, EPUB).

2. Automate the Boring Stuff with Python (automatetheboringstuff.com)

What it offers: Al Sweigart’s popular book available free online, focusing on practical Python applications for automation.
Content: Teaches Python through real-world projects like web scraping, working with Excel/PDF files, automating keyboard/mouse actions, and sending emails.
Why it’s effective: Motivation through immediate practical applications rather than abstract concepts.
Supplemental resources: Video course available on YouTube, practice projects, and forums.
Best for: Learners who want to see immediate practical applications of their skills.

3. Learn Python the Hard Way

What it offers: Zed Shaw’s controversial but effective method of learning through repetition and practice. The “Hard Way” refers to the disciplined approach, not difficulty.
Methodology: Based on the concept that typing code manually (not copy-pasting) builds muscle memory and deeper understanding.
Content: Covers basics through 52 exercises, each building on previous ones.
Free version: The older Python 2 version is free online; the updated Python 3 version requires purchase but the methodology can be applied with any resource.
Best for: Learners who benefit from structured, repetitive practice.

4. The Python Tutorial (Official Documentation)

What it offers: The official Python tutorial included with Python’s documentation.
Content: Comprehensive coverage from absolute basics to advanced features.
Style: More reference than tutorial, but excellent for systematic learners.
Best for: Self-directed learners comfortable with technical documentation.
How to use: Best as a supplementary resource rather than primary learning tool for beginners.

Phase 2: Building Foundations (Weeks 4-12)

Intermediate Learning Platforms

1. EdX’s MIT Introduction to Computer Science and Programming Using Python

What it offers: MIT’s famous introductory CS course, available free through EdX’s audit option.
Content: Computational thinking, data structures, algorithms, testing, debugging, and algorithmic complexity.
Difficulty: More challenging than typical beginner courses, with strong emphasis on computational thinking.
Format: Lecture videos, assignments, and exams.
Time commitment: 15-20 hours per week for 9 weeks.
Value: Provides computer science fundamentals beyond just Python syntax.

2. Coursera’s Python for Everybody Specialization (Audit Option)

What it offers: A 5-course specialization from University of Michigan, available for free when you audit the courses.
Content: Programming fundamentals, data structures, web data access (APIs, web scraping), databases, and data visualization.
Projects: Capstone project pulls together all concepts into a complete application.
Structure: Video lectures, quizzes, and programming assignments with auto-grading.
Certification: Free to access content; certificate requires payment.

3. Kaggle Learn’s Python Course

What it offers: Bite-sized lessons focused on data science applications of Python.
Content: Syntax, functions, lists, loops, and pandas for data manipulation.
Format: Interactive coding exercises in the browser with immediate feedback.
Unique feature: Integrated with Kaggle’s data science platform, allowing immediate application to datasets.
Best for: Those interested specifically in data science and machine learning.

Practice Platforms

1. Exercism’s Python Track

What it offers: Coding practice through increasingly challenging exercises with mentor feedback.
Content: Over 140 exercises categorized by difficulty and concept.
Mentor system: Free human mentors review your solutions and provide personalized feedback.
Structure: Download exercises, solve locally, submit for review, iterate based on feedback.
Best for: Developing problem-solving skills and learning Pythonic ways to solve problems.

2. Codewars

What it offers: Martial arts-themed coding challenges called “katas” ranked by difficulty.
Content: Thousands of challenges covering algorithms, data structures, language features, and puzzles.
Community aspects: See others’ solutions after solving, discuss approaches, earn ranks.
Learning method: Exposure to diverse problem types and clever solutions from other users.
Best for: Competitive learners who enjoy gamified practice.

3. HackerRank’s Python Domain

What it offers: Coding challenges specifically focused on Python skills.
Content: Basic to advanced challenges covering data types, strings, sets, math, iteration, regex, XML, and more.
Format: Solve problems in browser with test cases; view leaderboards and discussions.
Additional value: Many companies use HackerRank for technical screening, so practice here has career benefits.
Best for: Preparing for technical interviews while learning Python.

4. LeetCode

What it offers: Algorithm and data structure problems, many of which can be solved with Python.
Content: 2000+ problems with company tags, difficulty ratings, and discussion forums.
Focus: Interview preparation with emphasis on algorithmic thinking.
Python-specific: Many solutions and discussions feature Python implementations.
Best for: Intermediate learners focusing on algorithms and interview preparation.

Project-Based Learning

1. freeCodeCamp’s Projects

What it offers: Five required projects for their Python certification: arithmetic formatter, time calculator, budget app, polygon area calculator, and probability calculator.
Value: Forces application of concepts in complete projects rather than isolated exercises.
Structure: User stories provide requirements; automated tests verify correctness.
Support: Solution guides and forum community for help.

2. Real Python’s Project Tutorials

What it offers: While Real Python has paid content, they maintain an extensive collection of free project tutorials.
Sample projects: Build a Twitter bot, create a web scraper, develop a text-based game, make a website with Flask/Django.
Depth: Step-by-step instructions with explanations of why things work.
Best for: Learners ready to build complete applications.

3. Build Your Own X

What it offers: A GitHub repository listing tutorials for building various tools and applications from scratch.
Python projects: Build a blockchain, database, bot, web server, and more.
Learning method: Understanding systems by recreating simplified versions.
Best for: Learners interested in how things work under the hood.

Phase 3: Specialization and Advanced Topics

Web Development with Python

1. Mozilla Developer Network (MDN) Django Tutorial

What it offers: Comprehensive tutorial for building a web application with Django.
Content: Complete walkthrough of creating a library management website.
Prerequisites: Basic Python knowledge.
Value: Teaches both Django fundamentals and web development concepts.

2. Flask Mega-Tutorial (Miguel Grinberg)

What it offers: Legendary tutorial series for learning Flask, a lightweight Python web framework.
Content: 23-part series building a microblogging application (like a simple Twitter clone).
Depth: Covers templates, forms, databases, user authentication, deployment, and more.
Format: Detailed blog posts with complete code examples.
Best for: Those wanting to understand web development fundamentals before heavier frameworks.

3. Django for Beginners (William S. Vincent)

What it offers: The first few chapters of this popular book are available free online, covering Django fundamentals.
Content: Build a simple blog application, then a message board, and finally a newspaper site with user accounts.
Teaching style: Clear, practical approach with complete working examples.
Progression: Naturally leads into the author’s intermediate and advanced books (which are paid).

Data Science and Machine Learning

1. Kaggle’s Micro-Courses

What it offers: Series of short, focused courses on data science topics using Python.
Free courses: Python, pandas, data visualization, feature engineering, machine learning explainability.
Format: Brief tutorials followed by hands-on exercises with real datasets.
Environment: Browser-based notebooks require no setup.
Best for: Practical, applied data science learning.

2. Google’s Machine Learning Crash Course

What it offers: Introduction to machine learning concepts with TensorFlow and Python.
Content: 15+ hours of material including videos, written content, and interactive exercises.
Prerequisites: Basic Python and algebra knowledge.
Focus: Practical ML implementation rather than theoretical mathematics.
Best for: Beginners to machine learning with Python background.

3. DataCamp’s Free Intro Courses

What it offers: While DataCamp is primarily subscription-based, they offer free introductory courses in Python for data science.
Content: Introduction to Python, pandas, data visualization with Seaborn.
Format: Interactive coding in browser with video instruction.
Limitations: Only the first chapter of each course is free.
Best for: Sampling data science learning before committing to paid resources.

Game Development

1. PyGame Tutorials

What it offers: Official PyGame documentation and tutorials for creating games with Python.
Content: Setting up PyGame, drawing graphics, handling input, creating game loops, collision detection.
Learning path: Start with simple graphical programs, progress to complete games.
Community: Active subreddit (/r/pygame) for help and inspiration.
Best for: Visual learners and those motivated by creating games.

2. Invent with Python

What it offers: Al Sweigart’s series of books on game programming with Python, available free online.
Books include: “Making Games with Python & Pygame,” “Invent Your Own Computer Games with Python.”
Style: Project-based learning through building actual games.
Approach: Emphasizes understanding by modifying and extending provided code.
Best for: Complete beginners to game development.

Essential Supplemental Resources

Documentation and Reference

1. Official Python Documentation

What it offers: The definitive reference for Python language and standard library.
Sections: Tutorial, library reference, language reference, how-to guides, FAQ.
Best uses: Looking up specific functions, understanding language features in depth, exploring standard library modules.
Search tip: Often adding “python” and the module/function name to Google yields the relevant documentation page.

2. Python Module of the Week (PyMOTW)

What it offers: Detailed articles exploring Python’s standard library modules.
Content: In-depth examples of how to use various standard library modules effectively.
Format: Originally a blog, now archived but still extremely valuable.
Best for: Intermediate learners wanting to master Python’s built-in capabilities.

3. Real Python’s Articles and Tutorials

What it offers: While Real Python has premium content, they publish substantial free articles and tutorials regularly.
Content: Practical guides to specific tasks, deep dives into language features, best practices.
Quality: Exceptionally well-written and thorough.
Best for: Learning specific techniques or understanding Python concepts in depth.

Community and Support

1. Stack Overflow

What it offers: The largest Q&A community for programmers.
How to use effectively:
Search before asking (your question has likely been answered)
Learn to ask good questions (provide code, error messages, what you’ve tried)
Read answers to questions similar to yours
Follow Python-related tags
Value: Solutions to virtually every Python problem you’ll encounter.
Best for: Troubleshooting specific issues and learning from others’ problems.

2. Reddit’s r/learnpython

What it offers: Friendly community specifically for Python learners.
Content: Questions, project feedback, resource sharing, beginner-friendly discussions.
Rules: Encourages learning and discourages elitism.
Best for: Getting help in a less intimidating environment than Stack Overflow.

3. Python Discord Server

What it offers: Real-time chat with Python developers of all levels.
Channels: Separate channels for beginners, help, projects, various libraries/frameworks.
Value: Immediate help and community connection.
Best for: Quick questions and feeling part of the Python community.

4. GitHub

What it offers: Access to millions of Python projects’ source code.
Learning uses:
Read code from popular projects to see professional Python
Contribute to open source projects (start with “good first issue” tags)
Create your own repository to track learning progress
Best for: Learning from real-world code and building a portfolio.

Creating Your Learning Plan

Sample 12-Week Learning Path

Weeks 1-2: Python Fundamentals

Primary resource: Codecademy Python course or freeCodeCamp’s Python curriculum
Daily: 1-2 hours focused learning
Goals: Understand variables, data types, basic operations, simple functions
Practice: Complete all exercises in chosen course

Weeks 3-4: Control Flow and Data Structures

Primary resource: Corey Schafer’s YouTube series (videos 1-15)
Supplemental: Python for Everybody chapters 1-8
Daily: 1 hour video/content, 1 hour practice
Goals: Master lists, dictionaries, loops, conditionals, file I/O
Practice: Build simple scripts (to-do list manager, text analyzer)

Weeks 5-6: Functions and Error Handling

Primary resource: Automate the Boring Stuff chapters 1-10
Practice: Exercism Python track (first 20 exercises)
Daily: 30 minutes reading, 90 minutes coding
Goals: Write reusable functions, handle exceptions, debug effectively
Projects: Automate a personal task (file organization, data entry)

Weeks 7-8: Object-Oriented Programming

Primary resource: Real Python’s OOP tutorials (free articles)
Supplemental: Corey Schafer’s OOP videos
Practice: Codewars 8-7 kyu problems
Goals: Understand classes, inheritance, polymorphism, encapsulation
Project: Build a simple text-based game using OOP principles

Weeks 9-10: Working with External Libraries

Primary resource: Official documentation for selected libraries
Libraries to explore: requests (web), beautifulsoup4 (HTML parsing), pandas (data)
Practice: Follow library-specific tutorials
Goals: Install and use third-party libraries, read documentation
Projects: Web scraper, data analysis of public dataset

Weeks 11-12: First Substantial Project

Choose project based on interest:
Web: Simple Flask/Django app following tutorials
Data: Analyze dataset and create visualizations
Automation: Complex multi-step automation script
Process: Break into smaller tasks, implement gradually
Goals: Complete end-to-end project, use version control (Git), document code
Outcome: Portfolio piece to showcase skills

Time Management Tips

Consistency over intensity: 30-60 minutes daily is better than 8 hours once a week
Code every day: Even on busy days, write at least 10 lines of Python
Mix learning modes: Alternate between tutorials, practice problems, and projects
Take breaks: Use Pomodoro technique (25 minutes focused, 5 minutes break)
Keep a learning journal: Document what you learn, problems solved, ideas for projects
Teach others: Explain concepts to friends or write about them—teaching reinforces learning

Overcoming Common Challenges

“I’m stuck on a problem”

Take a break and return with fresh eyes
Search Stack Overflow with specific error messages
Try explaining the problem out loud (rubber duck debugging)
Simplify the problem or solve a smaller version first

“I understand concepts but can’t build projects”

Start with tutorials that build complete projects
Break projects into tiny steps
Copy working code first, then modify it
Don’t worry about perfect code—just make it work, then improve

“There’s too much to learn”

Focus on fundamentals first (master lists, dictionaries, loops, functions)
Learn what you need for your current project
Remember that even experienced developers constantly learn
Depth in core Python is more valuable than superficial knowledge of many libraries

“I’m not seeing progress”

Look back at code from a month ago—you’ll see improvement
Build a portfolio of small projects to visualize progress
Celebrate small wins (solving a difficult problem, finishing a tutorial)
Join a community to get feedback and encouragement

Beyond the Basics: Continuing Your Journey

Building a Portfolio

Start small: Simple scripts that solve actual problems you have
Graduate to complete applications: Web apps, data analysis projects, automation tools
Use version control: Host projects on GitHub from the beginning
Document your work: Write README files explaining what each project does
Contribute to open source: Start with documentation fixes, then small bugs

Preparing for Jobs

Master fundamentals: Data structures, algorithms, OOP, design patterns
Practice coding interviews: Use LeetCode, HackerRank, Pramp
Build domain-specific skills: Choose an area (web, data, DevOps) and deepen knowledge
Network: Attend local Python meetups (or virtual ones), participate in communities
Create a strong GitHub profile: Quality over quantity of projects

Staying Current

Follow Python news: Python Weekly newsletter, Real Python newsletter
Watch conference talks: PyCon talks are free on YouTube
Read Python blogs: Real Python, PyBloggers, Planet Python
Experiment with new features: Try new Python versions as they’re released
Continue learning: Computer science fundamentals, adjacent technologies, soft skills

Conclusion: Your Python Journey Awaits

The resources outlined in this guide provide everything you need to go from complete beginner to proficient Python programmer without spending any money. The key is not finding more resources—it’s consistently using the excellent free resources that already exist.

Remember that learning programming is a marathon, not a sprint. Progress may feel slow at times, but each concept mastered builds your foundation. The Python community is unusually welcoming and supportive, so don’t hesitate to ask questions and share your learning journey.

Your path might look different from others—some learn best through video tutorials, others through interactive coding, and still others through reading and experimentation. Try different resources from this guide to discover what works best for your learning style, then dive deep.

The most important step is to start. Open a tutorial today, write your first line of Python code, and begin building a valuable skill that can transform your career, enhance your problem-solving abilities, and open doors to creating technology that matters.

Python has changed millions of lives and careers. With these free resources and your dedication, it can change yours too. Happy coding!