Linear Algebra or Computer Science?

In summary, the conversation discusses the choice between taking a formal course in linear algebra or computer science (specifically, CIS 210 which focuses on Python programming) for an undergraduate physics student. One person suggests that learning Python would be more useful for obtaining lab opportunities, while the other emphasizes the importance of linear algebra in all types of physics work. However, both agree that learning both subjects is valuable and suggest taking an applied linear algebra course that incorporates scientific python, if available.
  • #1
Daniel Sellers
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I am going to have two slots available this year for electives and I want to use one of them for Astronomy. For the other, I am struggling to decide between Linear Algebra or Computer Science (CIS 210 at my university) which focuses on Python programming.

If I can only choose one, which is more useful for an undergraduate physics student? Both linear algebra and Python can be easily be studied online (I know because I have studied both online) but I've always appreciated the benefits of a structured class over independent study.

Anyone think that one is definitively more useful than the other? At least in a short-term academic context?
 
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  • #2
Learn to program. That will open the door to work in the labs of experimentalists much more than linear algebra.
 
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  • #3
Obtain a solid basis in linear algebra by attending lectures and getting live feedback on your work.
Learn Python programming by yourself from a good resource.

No matter what you will want to do (experimental or theoretical work), linear algebra is an essential part of the basis for any kind of quantitative science.
You can also use what you learn in linear algebra to experiment with NumPy.
 
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  • #4
So I have one reply saying that learning Python is the way to go because it opens up more lab opportunities ( I am planning to obtain some lab-based research experience next summer) and another reply saying that linear algebra is essential to all types of work as a physicist.

To be clear, I'm planning to learn both, and have been already. I'm just trying to decide which one is more worth taking as a formal course.

Thanks for the replies!
 
  • #5
Daniel Sellers said:
I'm just trying to decide which one is more worth taking as a formal course.
Yes, that was what I had in mind when I replied. I think these days both subjects are of great importance in quantitative work, and I do not want to underestimate the value of programming skills. However, when I think about which one is better taken as a formal course, I come to my conclusion as above.

Ideally, you would take a somewhat more applied linear algebra course that uses scientific python as a programming enviroment, but this may simply not be on offer.
 
  • #6
Krylov said:
Yes, that was what I had in mind when I replied. I think these days both subjects are of great importance in quantitative work, and I do not want to underestimate the value of programming skills. However, when I think about which one is better taken as a formal course, I come to my conclusion as above.

Ideally, you would take a somewhat more applied linear algebra course that uses scientific python as a programming environment, but this may simply not be on offer.

That makes sense, especially since applicable Python skills are likely to a be a part of my lab courses anyway. There is also a wide variety of Python tutorials and forums online from which to learn.

That helps, thanks again!
 
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Related to Linear Algebra or Computer Science?

1. What is the difference between linear algebra and computer science?

Linear algebra is a branch of mathematics that deals with the study of linear equations and their applications, while computer science is the study of computers and computational systems. Linear algebra provides the foundation for many algorithms used in computer science, but computer science also includes other topics such as programming, data structures, and algorithms.

2. How is linear algebra used in computer science?

Linear algebra is used in computer science for a variety of applications, such as image and signal processing, machine learning, computer graphics, and data analysis. It provides the tools and techniques necessary to represent and manipulate data in a concise and efficient manner.

3. Is linear algebra a necessary skill for computer science?

While linear algebra is not the only mathematical skill needed for computer science, it is a fundamental tool that is widely used in various areas of computer science. Having a solid understanding of linear algebra can greatly enhance one's ability to solve problems and develop algorithms in computer science.

4. What are some key concepts in linear algebra that are important for computer science?

Some key concepts in linear algebra that are important for computer science include vectors, matrices, linear transformations, eigenvalues and eigenvectors, and matrix decompositions. These concepts are used to represent and manipulate data and to develop efficient algorithms for solving various problems.

5. Can someone with a strong background in linear algebra excel in computer science?

Having a strong background in linear algebra can definitely be beneficial for excelling in computer science. It provides a solid foundation for understanding many core concepts and techniques used in computer science, and can also help with problem-solving and algorithm development. However, computer science also requires other skills such as programming and logical thinking, so a well-rounded understanding of both linear algebra and computer science is ideal.

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