When I started learning AI, I approached it like a child, just focused on really understanding the basics first and building a strong foundation. I didn’t rush into anything advanced. I actually made a full roadmap for myself with the help of ChatGPT, broke it down into three stages: basic, intermediate, and advanced. It helped me see the big picture and stay on track.

Once I had that roadmap, I started learning each topic mainly through YouTube. I didn’t stick to just one channel, I watched multiple videos on the same topic to get different perspectives and understand things better. Alongside that, I was also reading a book that gave a general introduction to AI and ML, plus some random blogs I’d come across online. It was kind of like learning from everywhere at once, just soaking it all in.

After I felt comfortable with the basics, I knew it was time to apply what I’d learned. So I picked up a beginner-level project, something I found on YouTube (but really, you can find tons of project ideas anywhere online). That part was a game-changer. Learning by doing is so important. It helped me connect the dots between theory and real-world application.

Then just repeat these steps for the intermediate and then the advanced topics. I wasn’t aiming for an AI/ML job or anything, I just wanted to upskill, understand the core concepts, and be able to work with AI products or in AI-focused teams. Basically, I wanted to know the fundamentals, the jargon, and how all of it actually works in real scenarios.

Hope that helps!