Can't Decide on Major for Computational Linguistics & AI

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In summary: This course will teach you a lot about what you need to know to get into a computational linguistics program.
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I am struggling to decide on a major, and I have two years left. I want to go into computational linguistics and AI. I cannot decide between linguistics, mathematics, computer science, and cognitive science. I'm sure about cognitive science, with a concentration in computation and AI, but I don't think that's enough to get into a computational linguistics program. I'm three courses away from a mathematics degree, but I have only B's and C's in all my math courses, which I am guessing would not look good. I am 7 courses away from a BS in computer science, but I don't enjoy every class which I'm required to take. As for linguistics, 5 easy courses. What do I do?
 
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If you want to seriously get into AI as a career choice, I'd go for Maths - with emphasis on Discrete Maths.

I think it's best not to specilise too early and the Maths will give you a more solid foundation than CS with a bit of discrete maths taught on top - plus you can teach yourself the programming language/architecture side.
 
  • #3
Math I think I'll defintely go with. As for programming, I know java, C, along with lisp/scheme, and I already have a minor in CS. But I love linguistics too and that's pretty easy for me I think. BTW, there's not many descrete math courses in our Math department. The only courses that come close to qualifying are modern algebra and probability theory.
 
  • #4
Certainly probability would be helpful - Bayesian statistics and all that...

Can you do any graph theory courses, or logic programming?

And they must teach basic set theory in the core Math degree...
 
  • #5
Logic programming and basic descrete maths are all taught in the CS department, I've had them. However there is also a course I'll be taking, Fundamentals of Computing Theory:
Fundamentals of formal language theory, computation models and computability, the limits of computability and feasibility, and program verification.
 

Related to Can't Decide on Major for Computational Linguistics & AI

1. What is computational linguistics and AI?

Computational linguistics is a field that combines linguistics, computer science, and artificial intelligence to study and develop computer systems that can process and analyze human language. AI, or artificial intelligence, is a branch of computer science that focuses on creating intelligent machines that can perform tasks that typically require human intelligence.

2. What career opportunities are available in computational linguistics and AI?

There are a wide range of career opportunities in computational linguistics and AI, including roles in natural language processing, speech recognition, data analysis, and machine learning. Some potential job titles include computational linguist, data scientist, AI researcher, and language modeler.

3. What skills are necessary for success in this field?

Success in computational linguistics and AI requires a combination of skills in linguistics, computer science, and mathematics. Strong problem-solving, critical thinking, and programming skills are also important. Additionally, a passion for language and technology, as well as the ability to adapt to new technologies and techniques, can also be beneficial.

4. How do I choose a major for this field?

Choosing a major for computational linguistics and AI will depend on your specific interests and career goals. Some common majors in this field include computer science, linguistics, mathematics, and data science. It may also be beneficial to take courses in related fields, such as psychology, philosophy, and cognitive science.

5. What are some resources for learning more about computational linguistics and AI?

There are many resources available for learning more about computational linguistics and AI, including online courses, textbooks, academic journals, and professional organizations. Some popular resources include Coursera, edX, and IEEE. Additionally, attending conferences and networking with professionals in the field can also provide valuable insights and opportunities for learning.

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