# Linear Algebra vs Deterministic Operations Research for CS

• Courses
• Of Mike and Men
In summary, the conversation focuses on the decision between taking Linear Algebra or Deterministic Operations Research for a CS degree with a mathematics minor. Both courses are considered important and foundational, but linear algebra is recommended as it is a prerequisite for many other topics and can be self-taught. It is surprising that linear algebra is not already a requirement for the CS degree and that it is not a prerequisite for the deterministic operations research course.
Of Mike and Men
Hey all,

I'm currently working on my CS degree with a mathematics minor. After this Fall, I will only have one more course to take to finish my minor.

I'm debating between Linear Algebra and Deterministic Operations Research. I do have other options, but these seem to be most applicable to CS.

Which would be more beneficial given my major?

If it matters here are the course descriptions:

Linear Algebra
An introductory course in linear algebra covering vector spaces, linear transformation, matrices, systems of linear equations, and inner product spaces.
Textbook: Linear Algebra and its Applications, Fifth Edition, by David C. Lay, Steven R. Lay, and Judi J. McDonald.

Deterministic Operations Research
This course provides a broad overview of deterministic operations research techniques. Linear programming will be covered including the simplex method, duality and sensitivity analysis. Further selected topics are from integer programming, dynamic programming, scheduling models, game theory, and associated topics
Textbook: Schaums Outline of Operations Research, by Bronson and Naadimuthu, 2nd Edition, McGraw Hill Schaums Outline Series. (The university notes that attendance is essential for this class).

Thanks.

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If mathematics belongs in any way to your final exam, then linear algebra at some stage is probably a must have. Otherwise operational research also contains to a large part methods from linear algebra, so you get some insights there automatically. So in my opinion it comes down to the question on how much mathematics you will need for your degree. I consider both of these two courses as equally important and basic and am surprised that they aren't mandatory.

If the choice is truly one or the other, linear algebra should be the natural selection. Linear algebra is foundational to many many things. Being able to speak in terms of vector spaces, takes a bit more time to grasp then self-teaching yourself the simplex methods.

Stephen Tashi
I agree with @MarneMath that if it's a choice between the two, linear algebra should be the one to take.

What I find surprising are the following:

1. The OP was able to make it this far in a CS degree without already taking linear algebra (in most programs I'm aware of, linear algebra is a requirement for completion of a CS degree).

2. That a deterministic operations research (OR) course won't require linear algebra as a prerequisite (I've taken an OR course in my undergraduate math program, and linear algebra was a requirement).

MarneMath

## 1. What is the difference between Linear Algebra and Deterministic Operations Research for CS?

Linear Algebra is a branch of mathematics that deals with the study of linear equations and their representations in terms of vectors and matrices. It is used to solve systems of linear equations and analyze linear transformations. On the other hand, Deterministic Operations Research for CS is a subfield of computer science that uses mathematical modeling and optimization techniques to solve real-world problems in areas such as resource allocation, scheduling, and network flow.

## 2. Which field is more relevant for computer science?

Both Linear Algebra and Deterministic Operations Research for CS are highly relevant for computer science. Linear Algebra is essential for understanding and implementing algorithms and data structures, while Deterministic Operations Research for CS is crucial for developing efficient and optimal solutions to complex problems in computer science.

## 3. Can you give an example of how Linear Algebra is used in computer science?

One example of how Linear Algebra is used in computer science is for data analysis and machine learning. Linear Algebra is used to represent and manipulate large datasets, perform dimensionality reduction, and train machine learning models such as linear regression and neural networks.

## 4. How does Deterministic Operations Research for CS benefit the field of computer science?

Deterministic Operations Research for CS helps computer science by providing a framework and tools for solving real-world problems in a systematic and efficient way. It allows for the optimization of complex systems and processes, leading to improved performance and decision-making.

## 5. Is knowledge of Linear Algebra necessary for understanding Deterministic Operations Research for CS?

While knowledge of Linear Algebra is not a prerequisite for understanding Deterministic Operations Research for CS, it is highly beneficial. Many concepts and techniques in Deterministic Operations Research for CS, such as linear programming and graph theory, are based on Linear Algebra principles. Therefore, having a strong foundation in Linear Algebra can greatly aid in understanding and applying Deterministic Operations Research for CS methods.

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