Want to study computer science and do computer engineering

In summary, the individual is currently studying physics and wants to pursue computer engineering with a focus on computer science. They are currently learning programming and looking for ways to expand their knowledge in other areas of CS such as algorithms, data structures, computer networks, and artificial intelligence. They are considering incorporating these topics into their PhD studies and are seeking advice on managing their time and learning these subjects. The speaker suggests starting with a programming language and learning about algorithms and data structures in the context of computer modeling, which would fit within the individual's PhD needs. They also mention the possibility of delving deeper into these topics after obtaining their PhD and suggest finding colleagues who can assist with other areas of CS.
  • #1
rahaverhma
69
1
I am now studying physics( B. Sc.) I want to do computer engineering and want to have in-depth knowledge of comp. Sci.. Because my interest lies there also.
So, please do tell me what should I I do now and in the future, now iIam doing my best by learning programming but want to do some other things also.
 
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  • #2
Try doing your physics problems numerically using hatever programming language you know. That's how I've always learned a new language.

Alternatively you could explore the processing.org website and learn some Java with interactive graphics with the processing environment. They have a lot of cool examples to check out.

Other alternatives are numerical Python or Julia and the anaconda distribution
 
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  • #3
Also try to learn algorithms. You may already have some knowledge about algorithms if you have done some programming but expand it as much as you can. CS is all about algorithms and a very effective way to learn good programming, is trying to implement algorithms in a gradual manner regarding difficulty. You can apply this strategy to your physics problems. Expanding to other fields of problems is also very important in learning algorithms. Also, data structures are of equal importance. An efficient algorithm requires efficient data structure(s) in order to construct an efficient program. Whether your goal is to go for computer engineering or theoretical CS after the basic undergraduate concepts, making the well known phrase in CS "Can we do better?" a part of your everyday vocabulary regarding the solution of problems, is in my opinion the way to go.
 
  • #4
I actually meant that in CS there are: Dis. Structures, data structures, computer networks, implementation of programming, operating systems, computer architecture, digital logic design, artificial intelligence, etc. I want to learn them all. And in my b. Sc only programming in c++is taught. So, again how do iI manage my time and could iI completely get all these before my P. HD.
 
  • #5
You can't learn them all in the time of your PhD without distracting from it. What you need are the fundamentals of algorithms and data structures. Everything else is built on those two subjects.

Operating systems are programs that manage and run other programs. They use a lot of tables to manage their resources and worry about paging memory, thread and process separation all done via algorithms and data structures. Computer networking was added to Operating systems as the OS capabilities extended to cooperate with other computers.

AI employs many kinds of algorithms and data structures to organize information and make predictions about what will happen.

...

So start with a programming language and begin to learn about algorithms and data structures perhaps in the conetxt of computer modeling which would fit within your PhD needs. The modeling work will bring in networking for distributed computing of your models, databases as you analyze big data... nd later you can consider delviing more deeply into these once you get your PhD.
 
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  • #6
rahaverhma said:
I actually meant that in CS there are: Dis. Structures, data structures, computer networks, implementation of programming, operating systems, computer architecture, digital logic design, artificial intelligence, etc. I want to learn them all. And in my b. Sc only programming in c++is taught. So, again how do iI manage my time and could iI completely get all these before my P. HD.
- Stay with physics and invent the sixty hours day first, or:
- move to biology and invent some brain enhancer pill, or:

- give up and pick just one or two from that list.
- additionally you can get some friends and colleagues who can do the rest for you.
 

1. What is the difference between computer science and computer engineering?

Computer science focuses on the theory and principles behind computers and their applications, while computer engineering combines computer science with electrical engineering to design and develop hardware and software systems.

2. Is computer science or computer engineering a better major for job prospects?

Both computer science and computer engineering have excellent job prospects, as they are both in high demand in various industries. It ultimately depends on your interests and which field you excel in.

3. Do I need to have prior coding experience to study computer science or computer engineering?

No, you do not need prior coding experience to study either field. However, having some basic coding knowledge may be beneficial in understanding the concepts taught in these majors.

4. What are the potential career paths for someone with a degree in computer science or computer engineering?

There are many potential career paths for someone with a degree in computer science or computer engineering, including software development, web development, data analysis, network engineering, and cybersecurity.

5. Are there any specific skills or qualities that are important for success in these fields?

Some important skills and qualities for success in computer science and computer engineering include strong problem-solving abilities, attention to detail, critical thinking skills, creativity, and the ability to work in a team.

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