3 Best Places to Learn Python Programming for Free

Python has rapidly grown over the years as one of the most popular, and most favoured programming languages. Github's annual report ranks Python in a consistent 2nd place over the last few years. Out of the top programming languages, Python's syntax is very easy to read and learn. New programmers and Computer Science students are often overwhelmed by the massive amount of information they need to learn, and Python provides a (relatively) easy way to ease into programming. Because of this, Python is very popular in first year college/university Computer Science curriculums.

Python is an important language in the world of programming, as it can be used in so many different domains - data science, web development, automation, and so much more. It's an in-demand skill that a growing number of employers are looking for, and with an average salary of over 95k in the United States, rest assured that learning Python is a great career move for those entering Tech.

It's hard narrowing down the list of free Python courses, since there are so many! We've decided to select a few courses that will help you learn Python easily, while giving you the knowledge to succeed in interviews. Many self-directed learners may not realize their shortcomings until they experience a tough technical interview, so be sure to round out your knowledge with both Python knowledge, Computer Science concepts, and domain specific knowledge.

1. Python for Everybody - freeCodeCamp

At almost 14 hours, this is a long introductory course. Many "Introduction to Python" courses are less than 4 hours, and although they may still cover the topic well, we highly recommend Python for Everybody by Dr. Chuck. You'll cover not only Python Basics, but several other important core topics that many Introductory courses don't cover. For example, working with JSON, Sockets, Databases, and more! Even if you never work with these topics again, having this core knowledge is extremely valuable. For example, socket programming and networking knolwedge carries over to other domains.

• Price: Free
• Paid Option : No
• Difficulty Level: Beginner
• Flexible schedule: Yes

Who should take this course? This is a good option for complete beginners who want to prepare for university-level courses, or who want to supplement their university-level studies. This is a beginner-friendly course with no prior experience necessary.

Link to the course - Python for Everybody

2. How to Think Like a Computer Scientist

Runestone Academy is an interesting option to learn Python, and for that matter, many other Computer Science topics. Aimed to "democratize textbooks" by offering textbook-like material for free, this indepth Python course skyrocketed their site popularity, and for good reason! This course offers more than just syntax; it offers a Computer Science student experience. You'll learn about many of the topics covered in college/university courses that many online courses today don't cover, such as recursion. This course is very indepth, so if you're up for it, expect to spend many hours completing this course.

• Price: Free
• Paid Option : No
• Difficulty Level: Beginner
• Flexible schedule: Yes

Who should take this course? This is a great option for self-directed learners who want a "college experience", and learn about many core concepts at a very involved, indepth level. This is a beginner-friendly course with no prior experience necessary, and after completing this course, you will understand many intermediate and advanced topics.

Link to the course - How to Think Like a Computer Scientist: Interactive Edition

3. Data Structures and Algorithms in Python - freeCodeCamp

Many programmers have a love/hate relationship with Data Structures. Seriously, how many have you used a Linked List outside of your college classes?

We're joking, of course. Data Structures have many use-cases, and can be the difference between an okay program versus an excellent program. Many technical interviews will ask about data structures, so even if you never use a Tree Data Structure in your day-to-day programming, it's incredibly valuable to understand them.

Equally as important are Algorithms (possibly even more important). An algorithm is a set of rules/instructions for solving a problem. A good algorithm is also fast and/or memory efficient, or provides some other unique benefit. This course covers several searching and sorting algorithms like quicksort, which are also crucial to not only build fast, efficient software, but for interviews as well. This course conveys so much awesome knowledge, expect to learn the material of 1-2+ college courses!

• Price: Free
• Paid Option : No
• Difficulty Level: Intermediate
• Flexible schedule: Yes

Who should take this course? This is a good option for those with a solid foundation of Python syntax who want to prepare for interviews, and who want to write the best code possible. Data Structures and Algorithms form the difference between a beginner and an advanced software engineer. They are also an important topic that employers love to see.

Link to the course - Data Structures and Algorithms in Python

What's Next?

Python is a great programming language for both new and experienced programmers alike. With amazing flexibility, existing code libraries to suit your every purpose, and easy-to-read syntax, Python is an important part of your programming toolkit.

New programmers often ask - "I've learned the basic syntax, what's next"? Once you've covered the basics, what you do next really depends on your goals. Typically, this may go one of two ways:

1. You are looking to enter the workforce as a Python programmer. You need to develop skills that employers want.
2. You are already employed (as a programmer, or otherwise), and you want to use Python to enhance or automate your work.

Depending on your goals, we recommend looking into these resources next:

• Web Development: Learn Django and Flask, two Python web frameworks.
• Data Science: You have a lot to learn next! Popular Data Science Python libraries include Numpy, Pandas, Matplotlib, Seaborn, and the list goes on. A combination of these libraries are used in modern Data Science pipelines. Plus, you should have foundational knowledge of research (e.g. forming hypotheses) and statistics.
• Machine Learning, you should learn the above Data Science libraries, plus Tensorflow and scikit-learn to start. Machine Learning is rapidly growing, so look for rising stars in the world of Machine Learning.
• Automation, or using Python to enhance your work: You have many paths to choose! We find ourselves using libraries such as Selenium, Robot Framework, Requests, and so much more, depending on the use-case. You can also use vanilla Python to accomplish these things, and libraries aren't always necessary. The book Automate the Boring Stuff by Al Sweigart has a lot of ideas for automation, and you'll learn a significant amount of Python along the way. Although a paid resource, you will regularly see coupons to receive this book for free on Udemy - keep an eye on Python-related subreddits, or Al Sweigart's social media.

Regardless of which path you choose, the best way to learn is to build projects. Once you have foundational knowledge of these tools, the best way to learn is to build your own projects. Find what interests you, and from there, the world is your canvas. (or rather, your code IDE is your canvas!)

Final Thoughts

Python is a fantastic programming language for several reasons: It has easy-to-learn syntax, it can be used for almost any purpose, and it is rapidly growing in popularity. It's an in-demand skills for employers, and by mastering Python, you'll be opening many career paths.

The resources in this article provide a solid foundation, but to really progress as a programmer, you must tackle your own projects. This can be overwhelming for beginners, but it's the best way to learn. Find what interests you, and create!