Internet is overwhelmingly crowded with study resources. While I admire them all, I can't help thinking it's easy for a beginner to get lost and never return.
I'm a self-taught Python programmer. And I've seen so many successful people doing the same. Python is super intuitive to understand and so powerful in its applications.
I'm glad that I chose Python.
I first learned Python through codeacademy.com. It was awesome learning it through their interactive system. But unfortunately, it's not free anymore.
While I still recommend it for most people I mentor, I have a list of other free resources.
Here is a curated list and why they are fantastic to take a look at. I hope this curated will help beginners finding the correct one for them.
I promise to tell you where I would start and progress if I were to start again. But before that, let's look into the modern options we have.
Scrimba: Free interactive python tutorial.
Why? Scrimba is next level in interactivity!
As in other platforms, a tutor will guide you through the course material. But you can pause the video and start editing the code on it.
That's the magic you see on Scrimba tutorials.
I was mesmerized when I first saw this. It almost takes you to a live classroom environment.
Interactivity alone does not make a great learning platform. Scrimba runs weekly coding challenges and adds new courses every month.
This is the kind of community you need to help grow in your programming journey.
Datacamp: High-quality Python Tutorials with built-in code editors.
Why? Specializing in Python for data science.
Python is fantastic for many applications. Data scientists are in love with it for its simplicity and applicability for a variety of problems. Because of it, Almost everyone aspiring to become a data scientist thinks about learning Python.
If data science is what interests you, Datacamp is the right place to be in.
You can select among many courses the one that suits you. You'll get to do an interactive exercise following a video tutorial from the presenter.
In addition to Python, you can also choose courses on R, SQL, etc.
Hackinscience: Learn Python through solving problems.
Why? Guided problem solving that gradually improving your Python coding skills.
If a lecture series is not your thing, you should check out Hackinscience.
Hackinscience is different from other websites on this list. It's a collection of interactive exercises organized into five groups; Basics, Training, Algorithms, Command-Line, and NumPy.
Hackinscience is a handy tool to solidify your learning that is worth checking out.
Sololearn: A Community to Learn Python.
Why? Solve challenges and learn by correcting each others' mistakes.
Contrary to its name, Sololearn is an excellent community for beginner Python programmers.
You have guided interactive courses for many other languages beyond Python. You can select the one and complete challenges to unlock the next level.
Yes, it's sounds similar to a video game.
Also, you can find courses for data science, machine learning, and web development as well.
If they don't fit you, try YouTube for best Python tutorials.
We also have quite a few awesome Youtube videos that are excellent for begin Python programming. I'd love to mention a couple of them, which I reviewed and recommended recently.
I highly recommend Mosh Hamedani's videos to everyone. He has made excellent video tutorials about lots of technologies, including Python.
Freecodecamp's youtube videos are another high-quality resource for those who want to learn Python. In my opinion, they are well organized and reviewed.
This is a tiny list of resources from thousands of articles, videos, and guided tutorials on the Internet. The good part is knowledge is freely available today.
Python is incredibly helpful for everyone regardless of what their profession is. If you're about to begin learning Python, I hope this list here helps you a lot.
Like, I promised earlier, here's what I'd do if I had to start over again.
If I were a complete newbie, I'd have started with Scrimba. It's a smooth interactive learning process. Parallelly I'd do the exercises on Hackinscience. This would give a solid understanding of the fundamentals.
Then I'd follow the courses on Datacamp to improve my data science-related Python coding skills.
Regardless of what I chose, I'd do the courses on Sololearn and participate in their community.