Today I'm going to be nerdy. I have spent a good part of the day working on my Python boot camp training, and I am enjoying myself immensely. There is something therapeutic about learning programming. Especially when it's such an easy-to-learn language as Python. It's fun to learn.
As I go in depth into the Data Engineering career path, Python is the language to learn. It is used in so many parts of the Data Engineering space, it's impossible to be a skilled data engineer without it.
Before I got laid off last June, I was beginning to experiment with Python at work. I was using it to pull and transform data from some cloud APIs to build simple reporting on users and user groups for one of the company's cloud applications. I was having a blast putting those scripts together.
Now that I am on my own, for now, I am jumping back into Python, but I am going to learn it the right way. The current course I am working through is a Udemy course on AI Engineering. As such, the beginning sessions are a great overview of Python for AI Engineering.
So far, I have covered environment setup, basic Python syntax and programming concepts, and now I am working through specific libraries related to data cleaning.
My most recent session was on Natural Language Processing and how one can clean up text by removing unnecessary words, replacing words and phrases, and stripping out punctuation.
This feels like the right next step toward building that portfolio—and maybe even some freelance work down the road. Nerding out on Python today was the highlight of a foggy day. If this keeps up, I might actually start enjoying the grind (not). Stay tuned—I’ll share what I build next.
—Daniel