This month’s T-SQL Tuesday invite comes from Todd Kleinhans, who invites us to discuss mastering a new or existing technical skill. Todd clarifies what he means by “mastering,” saying he’s referring to something that one is to develop over years rather than the latest trend that may come and go more quickly.
To read the full invite, click the T-SQL Tuesday logo.
Back to Basics
My workload has continued to include more software engineering work in addition to database work, so this year I wanted to put some emphasis on developing those skills. I thought about focusing on something programming language specific that I’m more familiar with, like Python or PowerShell, or continuing with TypeScript, which I more recently put some time towards studying.
I decided to think more broadly and put my focus on algorithms. Focusing on algorithms isn’t language specific, but it’s interesting to me, and it’s an area I feel like I can improve on.
Reading Levels
To get a bit of a refresher, I’m reading through Grokking Algorithms by Aditya Y. Bhargava. It seems to be more of a beginner-level book and will be a fairly quick read. I’ll go from one extreme to the other because after that book I’m diving into Intro to Algorithms by Cormen, Leiserson, Rivest, and Stein. I’m going from refresher mode with the first book to expert mode with the second book, which I’m fully expecting to be a challenge. I’m still far from an expert myself, but I’ll be better for trying.
Spaced Repetition
Along the way for both books, I plan to keep notes and create flashcards in Anki for spaced repetition learning. I’ve used these for multiple subjects over the years, ranging from databases like SQL Server and MySQL to cloud topics like AWS and Azure, along with various programming topics. It’s not perfect, and there is still some hands-on work needed to keep up with learning, but Anki flashcards have helped me be more comfortable retaining information and given me confidence that I’ll remember what I want to remember.
AI for Help
ChatGPT and Claude will likely be useful tools in breaking down concepts and creating coding examples to step through each algorithm for a better understanding. Considering what I’m focused on, I think it’ll be sufficient for experimenting with algorithms.
If I end up referencing YouTube for help, I’ll probably utilize NotebookLM to build out some FAQs and generate relevant flashcards in case there’s key information I want to note.
Never Stop Learning
Algorithms aren’t a trend that’s going to come and go. I may not take what I learn and use it every day, but I’ll have a deeper knowledge to work with as I progress in my career.
Thanks for reading!
Chad Callihan 