Advice for undergraduate students
There's an old saying: free advice is worth what you paid for it. There's something to that, and in any case you should make your own decisions. But we (meaning myself and several of my faculty colleagues) have put together a FAQ sheet giving you some things to think about as you plan your undergraduate career and beyond. None of this reflects official Stern or department policy, but we nevertheless believe it to be sound advice.
This is one of a collection of advice pages, all of them with the same theme: get skills, especially quant skills. They include advice for undergrads (this one), advice for MBAs (soon!), thoughts about data science (think "big data"), and advice for students who think they might be interested in applying to graduate programs in economics or finance.
Q1. What courses should I take?
NYU offers what you might call "the curse of choice": there are so many courses to choose from that it's hard to know where to start. We think you should take lots of things while you're here, expose yourself to a broad range of perspectives. But while you're doing that, leave some time to take courses that (i) have lasting value and (ii) develop skills that you can’t pick up yourself, either on the job or on your own. That’s the beauty of courses, they provide the structure for you to learn effectively.
We think quantitative courses would head the list. If you have a particular talent for math, you might want to take lots of them, but we think everyone would benefit from taking a few. You'll find that it's fun to have skills. Quant skills will also prepare you for almost any career you might choose: finance, consulting, marketing, or even working for a nonprofit or professional sports team. If that doesn't persuade you, look at all of these related links. If you're in a hurry, they say that people with quant skills get paid more. We know, money isn't everything, but this is information you might want to know up front.
To be clear: we're not suggesting you become a quant, although that's an option. But having even some basic quant skills will give you a new perspective on the world. And it's a useful perspective: quant skills are an identifiable source of differentiation that can get you the job you want, even if you go on to do other things. Here's my one-slide presentation with a shorter version of the same message.
Q2. What if I plan to go into finance or consulting?
Quantitative and data skills are invaluable in both fields -- and many more besides. It's no accident that banks, hedge funds, and consulting firms hire people with math and science backgrounds as well as business students. A business school education is a wonderful starting point, but business school + quant skills is an unbeatable combination. See, for example, this list of job openings at quantitative hedge funds. Some of them are for programmers, but others are for people with some quant skills -- maybe you!
Q3. Quantitative course options
Here's a quick overview, but if you're interested in information about specific courses, ask around. If you come up with good ideas of your own, please pass them on.
Programming and computer science. Everyone uses software in the modern world, but you're kidding yourself if you think that means Excel. You need to learn to write programs -- to code, as they say. As a Yale student put it: "Code is the lingua franca of the 21st century." If you don't believe us, ask Miss Disruption or the MathBabe. Or ask the head of the UC system, who says: "At Berkeley, about 70 percent of students are taking some computer science. At Stanford I think it's 90 percent, but that's Stanford. We're trying to introduce data science and data analytics into the core arts and sciences curriculum."
A good place to start is Introduction to Computer Programming (CSCI-UA.0101, uses Python). Or you could teach yourself Python; see our data science page. If you go beyond this, the language matters less than doing it. We see C++, Python, Matlab, and R used throughout the business world. See, for example, this speech about data analytics from the SEC.
Mathematics. The Stern School requires one semester of calculus, but we think you'd benefit from doing more than that. We recommend three semesters of calculus and one of linear algebra. (Or the equivalent: MATH-UA 211/212 Math for Economics seems to do all the above in two semesters.) They’re the foundation of economics, finance, and data analysis of all kinds. Once you’ve done that, you're well positioned to do lots of things. And perhaps even to understand that math is an art.
Data analysis. The modern world generates enormous amounts of data. Whatever you do in the future, it will be extremely helpful to you to develop the skills to make sense of it: programming, math, probability and statistics, data mining, and so on. Some people call the emerging field "data science," but whatever you call it, it involves marketable skills. See our guide to data science for more.
Q4. Are quantitative courses hard?
Grading in quantitative courses tends to be less forgiving than in less quantitative subjects. That's one of the reasons they're so helpful: you learn to think precisely and get clear feedback on whether you have done that.
Could this lower my GPA? Sure it could, although we find that many of our students do well in these courses. (Remind yourself: you're a good student or you wouldn't be here.) But even if your GPA falls, you'll expand your career options, raise your earning potential, and maybe even have some fun. Let us repeat: this will expand your career options. Businesses hire people who have skills that help them, and a GPA is not a skill.
One last thing: It can be a mistake to take quant courses that are too advanced -- and there are always courses that are too advanced. Take a course that stretches you but doesn't kill you. Once you’ve done that, you can take another one.
Q5. Anything else?
You can learn a lot outside the classroom -- and usually have some fun doing it. NYU is loaded with active student clubs, but we're more familiar with faculty activities. You have access to 200+ faculty members at Stern and many more throughout the University. Many of them are happy to include students in their work. Whether your interests are economics, finance, marketing, social psychology, or something else, you should be able to find a faculty member with similar interests who could use help in research or course development. Some students find that their experiences in such projects are the highlights of their undergraduate careers.
Q6. How can I find research assistant opportunities?
We suggest you do the following:
Lots of people have found work this way. Often you will have to start by working for free, but once you've established your value you may be able to get paid. But remember: the value here isn't the money, it's the experience.
There are also research opportunities outside NYU. Federal Reserve banks typically have both summer internships and full-time research assistant positions for students after graduation. Fed jobs are an established route to success: students who do this for a couple years often move to good jobs in industry or apply to graduate school. Many universities offer similar opportunities.
Q7. Should I take economics courses?
It's up to you, there are many routes to success. But economics provides a solid foundation whether you want to work in consulting, financial services, marketing -- or lots of other areas. If data provides information, economics provides a context for interpreting the information. NYU is blessed with two unusually strong economics groups, one at Stern, the other in the College of Arts and Science, as well as a world-class finance group. It's a resource you might want to take advantage of, whether you choose it as a concentration or just take a few courses.
Q8. How does the economics concentration work?
We wish we knew! The place to start is your advisor. If that doesn't work to your satisfaction, speak to Professors Foudy and Wachtel.
If you have other questions, stop by and say hello. I'll leave it to you to find the way.
(c) NYU Stern School of Business | #nyuecon | Address comments to Dave Backus.