A few months ago, I was honestly confused about where to start with AI. Every other post was hyping some shortcut or “guaranteed” path, and none of it felt real. I ended up starting with a Machine learning course mainly because I wanted clarity, not a title. I just wanted to understand what’s actually happening behind the scenes when people talk about AI. What surprised me was how much of artificial intelligence is about basics done right. Things like understanding data, training models, and figuring out why something works—or doesn’t. As I kept learning, I realized that an Artificial intelligence certification only makes sense when it comes after you’ve built that foundation. Otherwise, it’s just a line on a profile with no confidence behind it. I’m still learning, but the biggest takeaway so far is this: machine learning isn’t magic, and it’s not reserved for geniuses. It’s a skill you slowly build by making mistakes, revisiting concepts, and applying them in small ways. Once I stopped chasing hype and focused on learning properly, everything started to feel more manageable. If you’re exploring AI right now, especially from a beginner or career-switch perspective, you’re definitely not alone. A lot of us are just trying to figure out what’s worth learning and what’s just noise. submitted by /u/Hot-Situation41
Originally posted by u/Hot-Situation41 on r/ArtificialInteligence
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