The Loop Log

I’ve decided to bite the bullet and teach myself how to code. While I’m not aiming to become a full-time developer, adding a programming language or two to my résumé—and being able to demonstrate those skills—will significantly boost my chances of landing a QA or DevOps position at a software company.

I already work with SQL daily in my current role. I’m familiar with the Agile methodology and the Software Development Life Cycle (SDLC). Yet I’ve never tackled a general-purpose programming language (childhood BASIC doesn’t count).

After some digging around on my own, supplemented by talking to a couple of developers at work, I’m going with Python as my first language. The learning curve for a novice is apparently fairly moderate compared to some other languages, it’s a good place to start to learn programming fundamentals, and once you gain some proficiency with one language it opens the door to learning a second or a third.

To that end, I have installed Python on my machine, as well as Visual Studio Code (an IDE), set up a GitHub account, and have begun working through a popular beginner’s guide (Automate the Boring Stuff with Python) that I found online to get some of the basics down.

I completed the Introduction and Chapter 1 of the guide last night. There are 24 chapters in the guide. I have several more tutorials and other resources bookmarked for when I complete all the exercises of this intro guide. I will be documenting my progress on GitHub and hope to eventually have a few of my own custom projects there to build a small portfolio with.

I’ll say this, my initial impression from just the first chapter (and glancing ahead) makes me realize that having a background in SQL helps with understanding some of the core concepts. For example, I understand different data types, variables, the importance of proper syntax, and a few other principles that are being introduced in this guide. That was encouraging to discover.

I plan on hitting it hard for the next few months, doing something with the language every day. I’ll see what comes of it. I feel consistency, with hands-on practical exercises, will be the key to learning.

Here is my initial prioritized study plan for DevOps related technologies:

• Git (1-2 weeks) – Start here, you’ll need it for everything else
• Python fundamentals (4-6 weeks) – Continue your current path
• YAML (1 week) – Quick win, needed for upcoming tools
• Docker (2-3 weeks) – Practical and immediately useful
• AWS basics (3-4 weeks) – EC2, S3, IAM, basic networking
• Terraform (2-3 weeks) – Now you understand what you’re provisioning
• Kubernetes (4-5 weeks) – Complex but builds on Docker knowledge
• CI/CD platform (2 weeks) – Choose GitHub Actions for broad applicability
• PowerShell (ongoing) – Learn as needed for specific automation tasks