7 Practical GitHub Repositories That Will Teach You Python

Recent innovations in Artificial intelligence have catapulted Python’s popularity. People marvel at what AI can do, and the productivity benefits machine learning is bringing to the tech world.

Python programming powers many global industries, including data science, web development, finance, and security. It’s gradually becoming a sought-after tech skill.

There are many resources available online to learn Python programming. But not all are practical. These GitHub repositories all feature practical tutorials to boost your skills.

This repository lists programming tutorials for various languages, including Python. It has contributions from over 100 experienced software developers. As a learner, you will practice with tutorials and learn how to build applications from scratch.

The tutorials include various projects that allow a learner to practice Python-based skills. These include machine learning, web scraping and building bots, and web applications. You get to work on real-world projects and gain in-demand skills.

The tutorials use a combination of programming languages to create the projects. You, therefore, get to work with other languages and technologies alongside Python. So while learning Python, you get acquainted with other languages and communities.

This repository is the go-to place for Python Algorithms. Mastering essential algorithms is a skill every programmer should have. It contains many algorithms implemented in Python. The repo is an open-source community of programmers building new projects. They help each other with ideas and problem-solving. Their main goal is to work together to document and model helpful algorithms using code.

When you join the community, you practice and contribute to existing projects. They have social media accounts where developers communicate, debug and discuss projects.

The community keeps you updated with the latest Python programming news and guidelines. They also have repositories and communities of other modern programming languages.

A seasoned Python programmer named Asabeneh Yetayeh created this repository. It’s one of the many repositories he created for modern programming languages.

30 days of Python programming is a challenge for beginners to learn Python in 30 days. It’s a step-by-step guide that includes everyday challenges. As a learner, you have notes and exercises to test your learning at the end of each lesson. The exercises have categories 1-3 to test your understanding of the day’s concepts.

To earn a certificate, you must actively engage in the 30DaysOfPython challenge. There is a telegram group for anyone interested in the 30-day sprint. When you complete the challenge, you will earn a certificate. You also have the choice to learn the course at your own pace and take longer than the 30 days challenge.

As a learner, you can raise issues and contribute to the repo. The course has a star rating of 18000-star rating of GitHub, so it would be worthwhile to check it out.

This is a practical machine learning course by Siraj Vajal. It’s a 100-day challenge for machine learning enthusiasts. Siraj segments the course into notes and daily activities. This schedule exposes you to machine-learning concepts gradually.

You’ll start with introductory guides which cover topics like installation of the necessary Python tools and software. Later, you’ll advance to more complex concepts like decision trees and logistic regression. The guide provides the needed datasets and code you can use during practice.

Machine learning is a complex topic that you may find it daunting. This course teaches you the fundamentals at a slow enough pace to remain manageable.

This is a Python playground created by Oleksii Trekhleb and other contributors. It provides an interactive interface for you to change and add code to see how it works.

The repository encourages you to practice Python programming using the following steps:

1. Pick a topic you would like to learn or recap.
2. Read the instructions linked on the docstrings in the scripts.
3. Examine examples of code and assertions to see the expected output.
4. Change assertions, add and run the code to practice.
5. Run tests to see if it works correctly.

You can check your code against the provided Python code style guides. This helps to learn Python syntax and expressions through practice. It also improves the quality of your code. You can use the repo as a cheat sheet to recap statements and Python constructions.

This course by David Beazily covers the foundational aspects of Python programming. It emphasizes script writing, data manipulation, and organization of programs. The course is not for absolute beginners in programming. It targets developers with experience in other programming languages other than Python.

This course is part of David’s instructor-led courses. He uses the same course in Python for corporate training and professional development. As a learner, you will be learning and practicing on real-world projects.

The course helps you understand and work better with complex Python programs. You learn to write quality and modify or read code from other developers. It includes 25-35 hours of intense work, including hands-on coding exercises. But you also have the option to learn at your own pace.

Jeffery Hu created this repository for Python challenges. The repo includes 100+ Python exercises for users to test their programming skills. The exercises include exciting projects like creating games, translation programs, and manipulating features.

The repository includes accompanying notes that explain requirements and expectations. You can practice with these examples using the online IDE that runs in a browser. Jeffrey set up the IDE for beginners struggling to set up a local environment. It helps you to learn the language by practicing it as you read.

Why Learn Python?

Many developers regard Python as a beginner-friendly language. Its accessible syntax and efficient language structures bring a productivity boost. Python is versatile, making it useful in creating real-life solutions. You can use it in simple projects and complex projects like AI development.

Python improves with each release. The latest version, Python 3.11, has many improvements. There are new library modules and improved interpreters, among other enhancements. These improvements make writing code, debugging, and setting up projects easier.