Andrew Ng advises students pursuing AI careers to focus on coursework and technical skills. He emphasizes building a strong foundation in the fundamentals rather than chasing trends, and recommends hands-on projects alongside formal education to develop practical expertise.
If you want to pursue a career in AI right now, and let's say your child was entering Stanford, what advice would you give them in terms of how to spend their time?
So, you know, there's one thing that's actually really worth doing when you're Stanford students, which is take classes. Because it turns out that I feel like there's actually one pattern I see for both undergraduates and graduate students, including PhD students, which is there's so much exciting stuff to do, you just want to jump in and do it right. In fact, I've seen undergrads in their freshman year, you know, try to join a research lab and start doing work in AI. That's okay, nothing wrong with that. But it turns out that while project work is one way to learn, coursework is, I think, an even more efficient way to learn, especially when it comes to mastering the fundamentals, because professors will have put a lot of work to organize the material in a way that's efficient to, to, to learn and digest. So I would say, you know, take classes in, in AI technology or in entrepreneurship and gain those skills. I, I, I've seen students jump in and then if you are trying to work on the research lab without strong skills, you end up, you know, like labeling data or something, which is fine, you learn some things, but you actually learn a lot from, from taking courses. And then in addition to that, after you start to master the foundational skills, after you know how to use AI technology or Zen, and as you start to practice, find exciting use cases across campus. I do a lot of work over with people over in climate science or in healthcare to take my AI expertise and then marry it with a different discipline that I'm not expert in to find exciting applications. And hopefully that type of practice will help many of you find exciting projects to work on as well.
Do you need to take technical classes? Do you think you need to take computer science classes? If you want to pursue a career.
In AI, need is too strong. But I definitely encourage you to take technical classes. I think we're moving toward a world where, frankly, at some future point, I think everyone should learn to code. Or rather, I think it'll be useful for everyone to learn how to code for a couple of reasons. Everyone has access to data. This is different than the world used to be even a few years ago. And especially with generative AI, your ability to get something to work is much higher than ever before. The barrier to entry is much lower than ever before. And so if you learn just a little bit of coding, the amount that you really accomplish is significantly greater than if you don't know how to code at all.
