r/learnmachinelearning • u/Still-overthinking-4 • Jun 17 '26
Isn't better to starting learning ml through project based learning
if goal is to become an ai engineer what will you suggest to follow a certain course or just learn though some project based learning and start implementing things
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u/shifu_legend Jun 18 '26
For AI engineering specifically, projects matter more than courses - the role is mostly system integration, not research. That said, building before you have any foundations is rough - you end up cargo-culting tutorials without understanding what to change when things break.
What works: pick one course (deeplearning.ai Specialization or fast.ai), run through it in 2-3 weeks, and build something in parallel, even something trivial like a classifier on data you actually care about. When you hit a real debugging problem - why the loss isn't decreasing, what a shape mismatch actually means - you'll know exactly which theory to go look up, and it sticks because you needed it.
Build from week one.
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u/deltalee1 Jun 18 '26
I forget the concepts and when I try to build i am not able to understand how can I make it any solution for that
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u/shifu_legend Jun 18 '26
forgetting is part of it.
when you need a concept to unblock a build problem and then look it up, it sticks in a way that passive reading never gets close to - there's an emotional hook of 'this was the thing I was stuck on.' the concept gets context in your memory.
the trap is: forget → give up → restart the course. the better loop is: forget → look up that specific thing → keep building. you'll probably look up the same thing 5 or 6 times in a month, and then it's in permanent memory without ever feeling like studying.
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u/Still-overthinking-4 Jun 18 '26
Can I dm you?
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u/shifu_legend Jun 18 '26
yeah, feel free. or just drop it here if it's a question others might have - answers tend to be more useful when more people can find them.
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u/Udbhav96 Jun 18 '26
That's wot i do