Five ways to learn-relearn Python fundamentals

As someone who received formal training in data science in pre-deep learning era, I wanted to improve my skills in this field. I started by focusing on the basics of Python programming.

To ensure I had a well-rounded understanding, I decided to learn from multiple sources. Below are the resources I used and what I found helpful about each:

1. freecodecamp.org python course: This is a four-hour-long Python course video for beginners. While it is a good resource, I found that I had to pause the video frequently to try the code in Python interpreter. This made it difficult to stay engaged with the material, and I ended up watching more than trying. I recommend this course only if you are able to stop the video and try out each concept before continuing. Also, the long-form content was not the most effective way to learn.
2. Python 3 programming by codebasics: This is a better resource compared to freecodecamp.org. Each topic is presented in a short video, which makes it easy to skip over familiar topics and rewatch videos to reinforce concepts. The course also teaches debugging and introduces the PyCharm IDE. The channel recommends following the first 16 videos for beginners.

Both YouTube Python courses I used are free but difficult to follow as you have to pause the video and switch back and forth between YouTube and your Python IDE or interpreter. In contrast, the next three resources offer web-based learning that includes exercises.

1. Kaggle Python course: This course is designed with each lesson presented as a tutorial-exercise pair. The exercises are completed in a notebook, with your answers checked as part of the exercise. There are hints and solutions to the questions, which are helpful for learning. The only downside is that the course is more rudimentary compared to other courses.
2. AWS Workshop to learn Python: This is a good resource available for free from Amazon. The most important aspect of this workshop is that it forces you to complete tutorials on the AWS cloud, which provides exposure to AWS cloud services if you haven't used them before. Compared to other courses, this one teaches additional skills, such as logging, Amazon DynamoDB, and Amazon Lambda.
3. Microsoft Python for beginners course: This cloud-based resource does not require creating a cloud instance to complete tutorials. Instead, you use a sandbox environment. The course covers all basic topics, including functions and error handling. It also provides training on how to use Visual Studio Code IDE for Python. In addition to tutorials, the course also has knowledge checks in the form of multiple-choice questions of moderate difficulty level.

Overall, while the YouTube courses were free, they were challenging to follow as I had to switch between watching the videos and experimenting with the concepts in my Python IDE or interpreter. The web-based resources were more effective as the exercises were integrated into the learning process, ensuring I had to complete them to progress. Leaning from these resources helped with reinforcing the basic concepts and provided exposure to different python and non-python concepts-environments which I wouldn't have gained by following a solo course.

#pythonprogramming #python #dataanalytics #datascientist #backtobasics #cloudcomputing

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Below are the links to all 5 courses.