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Is learning AI/ML worth it?

I was searching about how can I learn AI/ML -self learning , so I discovered that it will take seriously large amount of time, So I want to know if it is worth it to learn it from MIT free resources and andrew ng courses and lex Fridman, Or should I wait and get cs degree and maybe a phd in ml, or should I choose different field, I am still young but I have some programming experience in web and python, so what should I do ?


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Daniel

Honestly, it feels like the AI/ML job market is completely locked behind advanced degrees right now. Most roles want at least a master’s or PhD plus experience. Unless you’re aiming for one of the big names (like FAANG or Nvidia) it’s tough to break in. Once the hype dies down, I think only those big players will still be pushing new AI projects.
              
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John

From what I’ve seen, having a Computer Science degree makes a huge difference. There are so many CS grads flooding the market that not having one almost instantly puts you at the bottom of a recruiter’s list. It’s like an unofficial hierarchy: PhD > Master’s > Bachelor’s > Diploma > no degree, and that really shapes how your résumé gets looked at.
              
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Léa

Even with experience, I’ve noticed that not having a degree can put you behind someone who does. It’s not everything, but it’s definitely a tiebreaker. It also helps with networking and just getting your foot in the door in places that still care about academic credentials.
              
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Ahmed

AI and ML aren’t something you can just “pick up” with a few YouTube tutorials. There’s a ton of serious math and programming involved. If you’re doing it just for fun, sure, learn casually, but if you actually want to work in the field, a proper degree really helps you get the depth you need.
              
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Jürgen

Not everyone agrees that AI is the gold rush it’s hyped up to be. I’ve seen people working in the field say AI is “basically worthless for anything serious.” And honestly, when you look at how much money companies like OpenAI are burning and how many businesses are already backing away from AI projects, it’s not that crazy of a take.
              
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Anastasia

Personally, I think generative AI is heading for a big crash. The burn rate is insane and there’s barely a path to profitability. It’s cool tech, but outside of the core ML research (like understanding neural nets), a lot of this stuff might not hold up long term.
              
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Pablo

ML as a field isn’t going anywhere. We already use it for tons of real stuff: fraud detection, facial recognition, auto-tagging, computer vision in manufacturing and defense, even video compression. The hype around LLMs can make people forget that ML already powers half the world’s tech quietly in the background.
              
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Tomasz

While everyone’s talking about an “AI bubble,” I actually think for real ML engineers and coders, this is just the beginning. Once the hype dies down and the prompt-engineered stuff fades, the demand for actual technical ML roles is only going to grow.
              
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Lena

If you’re getting into AI, I’d say focus more on learning how to implement it rather than building models from scratch. Training your own models is quickly becoming as easy as setting up an iPhone avatar; it’s knowing what to do with those models that’ll matter.
              
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Wei

Machine Learning looks super flashy from the outside, but at its core it’s just heavy-duty data science. You’re deep in probability, statistics, and linear algebra. If math isn’t your thing, you’ll probably hate it, but if it is, ML can be a really exciting space to work in.
              
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Category: Technology Enthusiasts

Subcategory: AI and Machine Learning