Hey, I’ve just completed the Python Learning Path on LinkedIn. It took me about 9 weeks. I could’ve got it done a lot faster, but it wasn’t my sole focus. I’m also learning the Django framework at the same time. Furthermore, please note that I’ve already covered Dr. Chuck’s Python for Everybody course before engaging in this new self-study.

A LinkedIn Learning Path is a collection of courses on a specific topic, or related topics, from one or more authors. From what I could see so far, these courses were not specifically designed to fit together, unlike pieces in a puzzle. This means that some information can overlap between the different courses you’ll cover. Moreover, you might love one instructor’s approach, while being close to hating another’s curriculum, pacing or lack of in-depth explanations. I humbly suggest that you keep your mind open and arm yourself with patience because there’s something to learn from each of them.

My opinion after having gone through all the chapters in this Python path is that it’s filled with a plethora of information, covering all that one needs to get from zero to hero. Well, maybe not hero, but you can certainly get from dummy to beginner level, while also covering some intermediate coding concepts. If you’ve never coded in your life, this is a good place to start.

The path consists of 9 courses for a total combined length of 19 hours and 6 minutes:

I especially loved the Python for Non-Programmers course by Nick Walter. It’s very accessible, with clear and easy to follow examples and explanations, an ideal beginning even for people with no coding experience. I’ve also loved the 3 course from the Programming Foundations series; they cover OOP (Object-Oriented Programming), data structures, and algorithms. Barron Stone’s Real-World Examples course is pure genius. He compares real-world objects and routines (e.g., making an omlette, brewing coffee, using the toolbox in your garage) to programming concepts. This is the easiest way to get your grasp on OOP that I’ve seen thus far.

Joe Marini’s materials are solid gold, although more advanced than the others. You might need to take your time for understanding algorithms and how to work with objects, their properties and methods. I did struggle a bit with his 2 courses, but it was worth it. Make no mistake, OOP continues to baffle me and I doubt this will change anytime soon.

I didn’t really click with the stuff from Kathryn Hodge, but it was an eye-opening journey through Python’s Standard Library and it should definitely be on your to-do list. However, my least favorite chapter was Ryan Mitchell’s Python Essential Training. In my opinion, the title is misleading. It’s anything but essential. I wouldn’t have placed it as the 2nd course in the learning path. The course is leaning more towards a seasoned programmer learning Python as a second language, not towards a beginner. Also, I personally disliked the challenge of building a drawing canvas.

Final course and the learning path’s end: Nail Your Python Interview, which is awesome! I just loved how Erin Allard combined the human side with data structures, runtime complexity and recursion. Some crucial notes on this one:

  • Teaching is one of the most effective learning tools; try to explain to a friend, a stuffed animal or  a rubber duck what you’re doing
  • Start applying for jobs before you feel ready; failure and rejection are part of the process (learn from all experiences, if you’re not the perfect match today, you might be tomorrow)
  • You shouldn’t wish for every company to hire you, you want the right company to hire you
  • Interview your interviewers; it’s about what they can offer you, not only about what you can do for them

I sincerely recommend giving a try to the Python for Everybody course, especially if you’re new to coding. Dr. Chuck’s experience as a Michigan University professor really shines throughout his materials. He’s there, holding your hand all the way. You rarely feel overwhelmed. Plus, he covers many real-world Python applications such as parsing xml and json, working with APIs and web-scrapping in an easy to digest approach.

This being said, while I didn’t resonate with every chapter from this learning path, I still find it to be a solid foundation for any aspiring Python programmer. And yes, you get a certificate of completion for each course and a certificate at the end for completing the entire path. With the gained knowledge, one could pass LinkedIn’s Python Skill Assessment.

Just keep learning.

Cheers!