Computer Science Niche for Mathematically Inclined Student

In summary, two students are discussing the options for a mathematically inclined person in the computer science field. The first student is a sophomore at a community college planning to transfer to UT-Austin for a double major in Mathematics and Computer Science. The second student, also a senior double majoring in the same fields, explains that there are many options within theoretical computer science that involve heavy math, such as computational complexity, automata theory, and information theory. He also mentions fields like scientific computing and artificial intelligence that require extensive knowledge of probability and statistics. The second student advises the first to take courses in discrete math and theoretical computer science, and mentions that robotics also involves heavy math. The first student is interested in pursuing a Master's degree,
  • #1
usem520
2
0
Howdy,

I am currently a Texas sophomore at community college. Attached in .DOC format is a list of the coursework I have completed by the end of this semester. I am planning to transfer to UT-Austin for the Spring 2012 semester with a double major in Mathematics and Computer Science.

I am posting here to ask for guidance as to where a mathematically inclined student might most comfortably land within the computer science field? I take into account both personal satisfaction and financial considerations, with regard to the former: the deeper the level of mathematics involved the better.

Thank you for your consideration.
 

Attachments

  • Classes.doc
    26.5 KB · Views: 228
Physics news on Phys.org
  • #2
I am a senior student also double majoring in Computer Science & Mathematics, so I can tell you that there are lots of options for a mathematically inclined person in computer science. Broadly speaking all sub-fields in theoretical computer science involve heavy math. These sub-fields can be roughly categorized as , Computational Complexity (What kind of problems can be solved by a computer) , Automata Theory (theory of abstract machines), Information Theory(quantification of information) , The theory of Algorithms and Discrete mathematics(Graph Theory, Number Theory, Cryptography and ...). There are also lots of fields that sort of fall under the above categories such as Quantum Computing, Parallel Computing and ...Also, you can get into a field called Scientific Computing (using computers to solve engineering and scientific problems) , however I think this is like a field in applied mathematics than computer science. Also, there fields in artificial intelligence that require extensive knowledge of probability & statistics such as Neural Networks, Machine Learning & Data mining.
For choosing your courses you should keep in mind that computer science math is a little different from the math required in fields such as physics. For computer science your courses should be more toward discrete math rather than analysis type courses. You should also take as many theoretical computer science courses as possible. A safe selection of math courses (which I also took) is:

Calc I, II
Linear Algebra I, II
Multivariable Calc
ODE's
Analysis on Manifolds
Abstract Algebra I, II
Intro to Combinatorics
Probability & Statistics I, II
Intro to Graph Theory,
Advanced Combinatorial Methods,
Intro to Mathematical Logic,
PDE's
Set Theory
Complex Analysis
Real Analysis
Topology
plus the theoretical computer science courses.
 
  • #3
Msh1 said:
Also, you can get into a field called Scientific Computing (using computers to solve engineering and scientific problems) , however I think this is like a field in applied mathematics than computer science.

Depends. Scientific computing is really broad, and under it's umbrella is usually a host of image processing, data mining, and machine learning techniques, so as often as not it ends up either in a CS dept or being done as part of an interdisciplinary team (usually x-infomatics is the buzzword thrown around for this type of thing.)

As an aside, robotics also has a heavy dose of math due to having figure out control and processing sensor data.

For computer science your courses should be more toward discrete math rather than analysis type courses.
Depends on the subfield. You want lots of stats and linear algebra for the machine learning/data mining/computer vision topics, logic is crucial for compiler design/language analysis/formal program verification/algorithms/(can't you tell yet that my school is big on logic at the graduate level), discrete math is important for computation/complexity/algorithms/, and some of the vision people and modelers really like their geometry and topology.

the deeper the level of mathematics involved the better.
What types of math do you like? And honestly, are you planning on tackling grad school? If not, from a purely practical point of view, it almost doesn't matter what you specialize in (though you may want to see what companies in your area want, and you may want to take the less math heavy applied courses-like web programming, software engineering, databases, and the like-or applied math/Cs stuff like image processing, data mining, and networking.)
 
  • #4
Msh1:

Thank you for the reply. I am glad to hear that such opportunity is available within computer science. Would the type of positions you describe generally be available within the privater sector, or are the more math intensive options generally found within academia?

story645:

Yes, I am definitely planning on getting an M.S. It is difficult to pinpoint the exact type of mathematics that I enjoy most since I have not yet taken upper division mathematics. However, I have thoroughly enjoyed my Calculus courses, and also to a lesser extent my Trigonometry and Algebra courses. I don't know exactly where my mathematical studies will lead, but I do know that I enjoy Mathematics too much not to pursue it further.
 
  • #5


I would like to congratulate you on your academic achievements and your decision to pursue a double major in Mathematics and Computer Science. You have chosen two fields that are highly complementary and in high demand in today's job market.

In terms of finding a niche within the computer science field, there are many options available for mathematically inclined students. One area that may interest you is data science, which involves using mathematical and statistical techniques to analyze and interpret large datasets. This field is growing rapidly and offers a combination of both mathematical and computer science skills.

Another option is to focus on algorithm design and analysis, which involves using mathematical principles to develop efficient and effective algorithms for solving complex problems. This area is highly technical and requires strong mathematical skills, making it a great fit for someone with a background in both mathematics and computer science.

You may also want to consider pursuing a career in artificial intelligence or machine learning, which involve developing algorithms and systems that can learn and make decisions based on data. These fields require a strong understanding of probability, statistics, and linear algebra, making them a good fit for someone with a mathematical background.

Ultimately, the best niche for you will depend on your personal interests and strengths. I would recommend exploring different areas within computer science and seeing which ones you find most intriguing and challenging. You can also speak with professors, professionals, and career counselors to gain more insight into potential career paths.

In terms of personal satisfaction and financial considerations, both data science and artificial intelligence/machine learning are in high demand and offer competitive salaries. However, it's important to also consider what you truly enjoy and find fulfilling in a career. With your background in mathematics and computer science, you have a wide range of options available to you and I have no doubt that you will find a niche that combines both your interests and skills. Best of luck in your future endeavors!
 

1. What is computer science?

Computer science is the study of computers and computational systems, including their principles, applications, and their impact on society. It involves both theoretical and practical aspects of hardware and software design, programming, and problem-solving.

2. How is math related to computer science?

Math is a fundamental part of computer science. It provides the necessary tools and concepts for understanding algorithms, data structures, and other key components of computer science. Many mathematical concepts, such as logic, probability, and discrete mathematics, are directly applicable to computer science and are essential for problem-solving and analysis in the field.

3. What skills do I need to have to excel in computer science as a mathematically inclined student?

As a mathematically inclined student, you likely already possess many of the skills needed for computer science, such as logical reasoning, critical thinking, and problem-solving abilities. However, you may also need to develop your programming skills and gain a strong understanding of data structures, algorithms, and discrete mathematics.

4. What career opportunities are available in the computer science niche for mathematically inclined students?

There are numerous career opportunities available for mathematically inclined students in the computer science field. Some common career paths include software engineering, data analysis, computer systems analysis, and information security. Other options include research and teaching positions in academia and industry.

5. How can I get started in the computer science niche as a mathematically inclined student?

To get started in the computer science niche, you can take courses in computer science and mathematics at your school or online. You can also participate in coding competitions, internships, and research projects to gain hands-on experience. Networking with professionals in the field and staying updated on industry trends and advancements can also help you get started in this niche.

Similar threads

  • STEM Academic Advising
Replies
23
Views
3K
Replies
1
Views
724
  • STEM Academic Advising
Replies
9
Views
3K
  • Programming and Computer Science
Replies
4
Views
1K
  • STEM Academic Advising
Replies
10
Views
1K
  • STEM Academic Advising
Replies
3
Views
1K
  • STEM Academic Advising
Replies
24
Views
2K
  • STEM Academic Advising
Replies
2
Views
928
  • STEM Academic Advising
Replies
7
Views
1K
  • STEM Academic Advising
Replies
4
Views
2K
Back
Top