Best complementary degree for computer science?

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Discussion Overview

The discussion revolves around identifying the best complementary degree to pair with a computer science degree. Participants explore various fields such as physics, mathematics, electrical engineering, and business, considering their relevance to computer science applications in areas like robotics, artificial intelligence, and data science.

Discussion Character

  • Debate/contested
  • Exploratory
  • Technical explanation

Main Points Raised

  • Some participants suggest that physics complements computer science well, particularly for applications in programming and simulations, while mathematics is also considered beneficial for developing problem-solving skills.
  • Others argue that while mathematics is valuable, many employers prefer degrees that provide a broader range of job opportunities, such as business or engineering.
  • Electrical engineering is mentioned as a potential complementary degree, especially for those interested in software that supports hardware products.
  • There is a discussion about the rising demand for applied mathematics skills, particularly in data science and machine learning, suggesting that a math degree could be advantageous when combined with computer science.
  • Concerns are raised about the job market for math majors, with some participants emphasizing the importance of diversifying one's studies to enhance employability.
  • Participants share insights on the current job trends in data science, noting the need for industry-specific knowledge and the importance of aligning data science skills with business objectives.

Areas of Agreement / Disagreement

Participants express differing views on the value of mathematics versus other degrees as a complement to computer science. While some advocate for mathematics due to its applicability in data science, others caution against its limitations in the job market. The discussion remains unresolved with multiple competing perspectives.

Contextual Notes

Participants highlight the importance of applied mathematics skills, particularly in advanced statistics, for careers in data science. There is also mention of the need for subject matter expertise in specific industries to enhance job prospects.

member 624364
What would be the best degree to have along side a degree in computer science? I am thinking it is either physics or mathematics.

My interests involve, robotics, artificial general intelligence, 3D graphics, computer vision, neural nets, file compression and aerospace engineering(It’s an interest, although I am not very good or knowledgeable on it currently :P).
 
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Physics complements Comp Sci well for applications programming or computer simulations programming. Calculus and Linear Algebra would cover the 3D graphics, computer vision, neural nets background. Some engineering courses like mechatronics and mechanics would cover robotics. Computer Science AI courses would cover the background for AGI, neural nets and computer vision.

Aerospace would need the same math as needed by a physics major in addition to some aeronautics design courses and others that I can't think of yet.

Matlab would be a good thing to know too as its used extensively in engineering courses in my university.
 
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Not the most accurate information here but: Once I was talking with a CS instructor and he told me that the best grades in any CS class are from Math majors.

Math, in my opinion, is a great choice. If you still have any elective to spare maybe give physics a go. I feel that CS requires more intuition than methodology since every problem is a new one and math can offer you a new way of thinking, however in physics it is more about systematization and using mathematical tools.
 
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I wouldn’t say math because most employers are looking for other kinds of degrees where computer science complements them. Math majors are more limited in their choices in the job market. Many businesses hire business majors and those with comp sci backgrounds are in high demand than business majors alone.
 
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Electrical Engineering? How do you store your software without hardware?
 
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YoshiMoshi said:
Electrical Engineering? How do you store your software without hardware?
I wouldn’t say EE either unless you were working for a hitech firm that wrote software to support their hardware product or some similar business model.

Basically it depends on what jobs you are interested in and plan to pursue once you graduate. Your backup plan should include courses to give you the edge in any job interview by knowing something of the field and it’s terminology.

When I considered this issue many years ago, I chose physics with comp sci as my backup because of personal interest with it’s many possibilities and it worked well for me at that time. This was before the glut of comp sci savvy graduates we have now so you need to do more to stand out.
 
jedishrfu said:
I wouldn’t say math because most employers are looking for other kinds of degrees where computer science complements them. Math majors are more limited in their choices in the job market. Many businesses hire business majors and those with comp sci backgrounds are in high demand than business majors alone.

I must take issue with your assessment above. With the rise of data science and machine learning positions in industry, many employers are looking for people who not only have software development/coding experience, but someone who has the complementary mathematical abilities to begin to develop algorithms to analyze such data. This would imply that someone with, say, a degree in math (or some cognate field) alongside computer science would be in high demand.
 
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StatGuy2000 said:
I must take issue with your assessment above. With the rise of data science and machine learning positions in industry, many employers are looking for people who not only have software development/coding experience, but someone who has the complementary mathematical abilities to begin to develop algorithms to analyze such data. This would imply that someone with, say, a degree in math (or some cognate field) alongside computer science would be in high demand.

I agree but they are not looking for math major math skills but rather more applied math skills mostly advanced statistics. I know many folks who have various STEM degrees going into Data Science because its the next BIG thing but I worry that if you throw your eggs into this basket then it'll become an issue later on in your career.

You must diversify your major enough that you can use your computer skills in other areas too.

Here's an article on the recent Data Science trend with many unhappy about the career.

https://towardsdatascience.com/why-so-many-data-scientists-are-leaving-their-jobs-a1f0329d7ea4

and this one about prepping for a job in the field:

https://towardsdatascience.com/the-two-sides-of-getting-a-job-as-a-data-scientist-a4571acc58bc

Here's Glassdoor's take on job trends where while AI is taking industries by storm, you will need some knowledge of the industry (finance, healthcare) and its terminology to be successful as an AI developer or Data Scientist.

https://www.glassdoor.com/blog/5-big-trends-in-jobs-for-2018/
 
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jedishrfu said:
I agree but they are not looking for math major math skills but rather more applied math skills mostly advanced statistics. I know many folks who have various STEM degrees going into Data Science because its the next BIG thing but I worry that if you throw your eggs into this basket then it'll become an issue later on in your career.

You must diversify your major enough that you can use your computer skills in other areas too.

Here's an article on the recent Data Science trend with many unhappy about the career.

https://towardsdatascience.com/why-so-many-data-scientists-are-leaving-their-jobs-a1f0329d7ea4

and this one about prepping for a job in the field:

https://towardsdatascience.com/the-two-sides-of-getting-a-job-as-a-data-scientist-a4571acc58bc

Here's Glassdoor's take on job trends where while AI is taking industries by storm, you will need some knowledge of the industry (finance, healthcare) and its terminology to be successful as an AI developer or Data Scientist.

https://www.glassdoor.com/blog/5-big-trends-in-jobs-for-2018/

Thanks for the links. We are actually in agreement that what people in industry are looking for are applied math skills (in particular advanced statistics), but these are skills that are relatively easy to acquire for someone with a math major, especially when combined with a CS major. And it is indeed true that people with a variety of STEM degrees would also have the requisite technical skill sets to break into data science.

I fully agree that one needs to diversify one's studies beyond core computer science skills (I think taking a broad swathe of courses in addition to a math and computer science degree would do the trick).

Now in terms of the actual links. I fully agree that applicants interested in pursuing data science positions need to have a realistic perspective of what the overall job environment is like and what actual impact their contributions are likely to have (which tends more often than not to be incremental). The flip side is that businesses need to also have a carefully thought plan to see how data science can properly align with their overall business objectives.

I especially like the second link and the advice in prepping for a job. Much of the advice isn't unique to data science but really any STEM job.

As for Glassdoor's take on job trends with respect to AI, I'm surprised that AI-related firms have not penetrated into financial services to the extent that I would have expected by now (the fact that Glassdoor is suggesting big changes are set to take place in 2018 implies that these have not occurred as of yet), but that may be because I happened to have been paying attention to both the scientific press and publications about algorithmic trading. I'm also surprised that HR firms have not taken more advantage of data science or AI, given the sheer quantity of data they would have gathered regarding potential applicants.

I do agree that some subject matter expertise (be they finance, health care, or human resources) is important for aspiring data scientists -- however, my own opinion is that it is usually fairly easy for someone with a quantitative background (such as math, CS, physics, etc.) to pick these up relatively quickly.
 
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I vote for operations research in an engineering department. It would have a good mixture of optimization, computer modeling and simulation, and statistics. So many things of interest have some random behavior, need to be modeled in a computer simulation, and people what to optomize them.
 

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