Useful majors for postgrad study in machine learning and AI

In summary, to become a successful machine learner, you should study math and computer science. You can also study cognitive science and neuroscience if you want to focus on understanding how the brain works.
  • #1
yojoe
3
0
Hello, I'm wondering what sort of areas would be useful in postgrad study in machine learning and AI. At the moment I'm in Arts majoring in mathematics and logic/philosophy of science. I'm planning to keep these two majors, as statistics and discrete mathematics will be useful in AI/machine learning, and the decomposition of natural language into symbolic logic would also be useful. What else would be a practical major in my toolbox?

I'm planning to pick up either a science degree (with a major in computer science and physics) or an engineering major like electrical engineering, as it is so broad of an area.

Can anyone who has done computer science inform me if that would be the correct path to take? Should I be double majoring in Computer science? I'd kinda like to pick up the physics as well because it interests me. Are there any other majors I should be looking at, but missed?

Thanks.
 
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  • #2
AI and machine learning are usually considered subfields of computer science. If that's what you want to study, that's where you should be.
 
  • #3
I'd study math and then you could get a graduate degree in CS
 
  • #4
A lot of people in machine learning have mathematics backgrounds. This is especially true as you move farther from the "applied" branches of the subject and into statistical learning theory (Vapnik-Chervonenkis theory) and related more mathematical areas.

You'll also see a lot of people with background / interests in cognitive science / neuroscience. A lot of the best research groups, especially the more mathematical ones have a significant interest in this area. I myself am a graduate student in one of these groups. My undergraduate background was in Neuroscience, Mathematics and Philosophy.
 
  • #5
Hi everyone. I hope that it is ok that I drop in on this thread. I'm also very interested in machine learning, but am a maths major.

I was wondering, should I be taking more linear algebra papers, or more analysis? I understand that measure theory is important in understanding the workings of probability theory so a lot of analysis right? But after looking around, I've seen people mention that abstract algebra would be useful to know too.

My goal at the moment is to get into grad school so I'm trying to sort out the prerequisites so that I'm ready for it.

Cheers
 

FAQ: Useful majors for postgrad study in machine learning and AI

What are the most useful majors for postgrad study in machine learning and AI?

The most useful majors for postgrad study in machine learning and AI include computer science, mathematics, statistics, engineering, and data science. These majors provide a strong foundation in programming, quantitative analysis, and problem-solving skills, which are essential for pursuing a career in machine learning and AI.

Is a graduate degree necessary for a career in machine learning and AI?

While a graduate degree is not always required, it can greatly benefit those interested in pursuing a career in machine learning and AI. A master's or PhD program can provide advanced knowledge and skills in the field, as well as opportunities for research and networking with industry professionals.

Are there any specific courses or concentrations within these majors that are particularly useful for machine learning and AI?

Yes, there are several courses and concentrations within these majors that are highly relevant to machine learning and AI. Some examples include courses in programming languages such as Python and R, courses in data mining and analysis, and concentrations in artificial intelligence or machine learning.

Are there any other majors that can also be useful for a career in machine learning and AI?

Yes, there are other majors that can also provide a strong foundation for a career in machine learning and AI. These include economics, psychology, and cognitive science, as they involve data analysis and understanding human behavior, which are relevant skills in the field of AI.

Is it necessary to have a background in both computer science and mathematics for postgrad study in machine learning and AI?

While having a strong background in both computer science and mathematics can be beneficial, it is not always necessary. Many graduate programs in machine learning and AI are interdisciplinary and accept students from various backgrounds. What is important is having a solid foundation in either of these fields and a passion for learning and problem-solving in the field of AI.

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