How difficult is it to jump into a career for CS regarding specific branches of it?
I'm a high school senior seeking to pursue a major in Computer Science in college/university because I'm passionate about a particular branch in CS, AI. As AIs are becoming more practical, intelligent, and utilized, I'm fascinated by all the capabilities that AI has across a spectrum of disciplines. As AI is a specific concentration in CS, there are uncertainties on how I should approach my career in university, and after university. #computer-science #college
As for what degree do you need, I'd argue you don't need to worry about this too strictly, choose something you enjoy and will be engaged with you are going to be studying this for 3/4 years, so you need to be interested and enjoy the subject. Not everyone in AI has a computer science degree, anything from chemistry, physics, mathematics or engineering can lead into a career in tech or AI. What's more important is choosing a well respected university/college and course which you are going to enjoy and do well in.
I started out doing physics at university and my final year project involved AI and Bayesian methods as this was something I was interested. Most course have some degree of flexibility to allow you to choose your own path, and it's the same with your career afterwards. Pursue what you enjoy and keep an ear to the ground for the industry trends, and your career can evolve into whatever shape you want it to.
I'll try to answer this purely from undergrad coursework and how you could go about structuring your education in college. The first part of that is finding a good college and while good can mean a lot of things for a lot of people, my recommendation would be to find colleges which are popular for their CS and data science programs. Since AI is specialized field of CS, having strong fundaments in CS and data would give you a good foundation to pursue AI. Additionally, when considering colleges look at the coursework(good balance of real world projects and research), professors(their research in AI), and alumni(are they pursuing AI?), this will help you compare colleges.
Next, during your undergrad, complement your learning at school with projects. I can't stress this enough and is probably the most important. If the coursework doesn't have a project, find an AI problem and kick start a side project that can help you learn. If the university isn't offering an AI/data course during a semester, then learn online(coursera, udemy etc). Long story short being, keep learning, and keep applying your learnings to solve problems around you.
As Lupita mentioned, internships are a great way to learn from industry experts, so take the time and definitely explore them as well.
Cheers and all the best.
When you're a student, you can try to find internships related to our interests and maybe even work with your team to build an exciting internship project specifically with AI. Also, if you try to find some companies that are leaders in the AI space, that would be a great place to start looking for internships! When building your class schedule, look for any electives related to AI or, reach out to any professors in your university doing interesting research (and maybe you can join them!)
Lupita recommends the following next steps:
a) All else being equal pick a CS program with a large AI group or groups. You can filter http://csrankings.org/#/index?none&us for schools with a lot of publications in different AI topics.
b) For interdisciplinary AI most research universities will have Professors in Molecular Biology working on Computational Biology with AI, etc. Most science/analytical disciplines have a Computational ??? area, e.g., Computational Chemistry, Computational Physics, Computational Finance etc. As an undergraduate student working in a interdisciplinary lab that does <Pick your science> + AI is a good option.