I’ve been a backend developer for years, but since 2022, my curiosity about machine learning has been growing steadily. As a software engineer starting my journey into machine learning, I’ve faced doubts and impostor syndrome — wondering if I had what it takes to learn data science and ML. Now, I’m taking a bold step forward by enrolling in my first data science course. In this post, I’ll share my experience transitioning into machine learning and how I plan to merge my backend skills with ML engineering.
I’ve been a backend developer for a while now — building APIs, writing logic, organizing databases, and making sure everything runs smoothly under the hood. And honestly? I love it. I love the clarity of structure, the satisfaction of writing clean, working code, and the quiet joy of shipping features that just work.
But since around 2022, something else has been tugging at my curiosity: Machine Learning.
At first, it was just that — curiosity. I’d see projects that used ML to detect diseases, recommend content, generate text (hello, ChatGPT) and even write code (give it up for Cursor), and I’d think, How do they even do that? So I started researching. What do ML engineers actually do? What skills do they need? How does it all work?
I’d dip my toes in — maybe read an article, bookmark a course, try a tutorial then quietly step back.
Maybe it’s too math-heavy. Maybe I don’t belong here. Maybe I should just stick to what I know.
Classic impostor syndrome. It hit hard, and it hit often. So I stayed in my lane, even though that curiosity never really went away.
But something shifted recently.
I realized that I don’t need to have it all figured out to start. I don’t need to be a math genius or a Kaggle Grandmaster on day one. What I do need is to start — messy, imperfect, unsure, yeah,but start anyway.
And that’s exactly what I’m doing.
Next week, I begin my first proper data science course at ALX Africa. (Here’s a post on how I discovered them and enrolled). For real this time. No more just watching from the sidelines. I’m showing up, I’m learning, and I’m giving myself permission to grow slowly and steadily — and to get things wrong along the way.
I still love software engineering. That’s not changing. In fact, one of the things that excites me the most is finding ways to merge both worlds — applying machine learning principles into the systems I already love building. I’ve recently learned that there’s actually a name for that: AI Engineering. And eventually, that’s where I want to land — using both my backend expertise and ML skills to build smart, impactful systems.
So yeah, curiosity got me here. And fear tried to keep me away.
But I’m choosing to stay — to explore, to learn, and to grow.
If you’re just starting out in ML/AI and feeling overwhelmed too, you’re not alone. Let’s figure it out together.
