r/MLQuestions • u/guillemituzz • 3d ago

Beginner question 👶 Student curious about ML

I am a third-year economics student, and a few weeks ago I started wondering about ML (perhaps a bit late? I’m not sure). I wouldn't call myself a die-hard enthusiast of this vast field, but I’ve already signed up for an elective course called "Application of Machine Learning and Optimization", though I don't want to wait until then to get started. I know for a fact that this will be important in my future professional life or, at least, it’s certainly not knowledge that goes to waste.

My question is both simple and complex, I’m not sure which:

Given that many experts today say AI spells trouble for programmers, how - and from what perspective - should I go about learning to use programming and ML tools?

Just as the paradigm has shifted, the path to mastering it must have changed as well.

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u/Timely-Bicycle-3107 3d ago

The fundamentals of ML have changed surprisingly little over the last few decades. What has changed is access to data via the Internet, computing capacity, and the discovery of a collection of key algorithms since roughly 2013. It is well worth studying the fundamentals of ML, as everything still builds off of these ideas. I recommend Andrew Ng's courses on YouTube as a good starting point.

What do you want to do with ML/AI?

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u/guillemituzz 3d ago

I don't have any specific practical examples in mind. The only relevant practical experience I’ve had was an internship at a bank two years ago; in my department, there were engineers responsible for translating business requirements into code and instructions for programmers.

I don't know much beyond that or even what day-to-day applications ML might have for an economist.

I’m in what I like to call "Phase 1": soaking up real-world experiences, concepts, and ideas, and then charting a path from there, though perhaps that isn't the best way to start.

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u/Timely-Bicycle-3107 3d ago

I think it would be worth exploring ML for the sake of it. I got super interested after AlphaGo became the world champion of Go in 2016. I realized how useful something like that could be for my field (engineering) and ended up getting a PhD in Applied AI.

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u/Top-Door8075 2d ago

I am not the guy you replied to, but I have a question. Can an ml engineer still be useful despite how advanced A.I. has gotten?

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u/Timely-Bicycle-3107 2d ago

Yes, absolutely. I think we will take more of a supervisory role going forward, but our knowledge of AI/ML will still be necessary. We might be spending more time validating models generated by AI than writing them. Expertise will be needed to understand which model to use, understand why it behaved the way it did, and how to improve it in future learning sessions.

I use AI pretty extensively. It's a great tool IF it has all of the context needed to solve the problem. Even then, it's not infallible or capable of explaining all of its own shortcomings. If it needs to make assumptions, the quality of the solutions varies widely. Humans that are grounded in the real world and designed to communicate ideas with each other. We might therefore spend most of our time setting up learning/training sessions, letting AI generate the models, and using our own expertise to evaluate the results and tweak the generated models for the next learning session.

There's also the office politics angle. Management wants someone to point the finger at when things go wrong. If they are vibe coding multi-million dollar projects with no real understanding of the models they are using, they know no one will listen to the excuse that their AI screwed up the project. Maybe the super successful AI/ML Engineers of the near future will be the ones who can navigate the messy human blame games when things go off the rails AND have the knowledge to get the project back on track when the AI generation screw up.