Why EVERYONE Should Take Data Science for Everyone: Interview with Professor Andrea Jones-Rooy

NYU Center for Data Science
6 min readJun 16, 2020

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Data Science for Everyone is the gateway into the world of data science for anyone who has asked them themselves “What is data science anyway?” This summer CDS decided to offer this popular course in a unique asynchronous format where each lecture takes the form of three short videos that can be watched whenever students can make the time for it during their day.

With the success of the first summer session of the course, which began in May, CDS has decided to offer a second summer session that starts in June. In anticipation of this second offering, CDS Social Media team member, Colton Laferriere, talked with Professor Andrea Jones-Rooy about how the first session was developed, what the class is like, and why everyone should sign up for Data Science for Everyone!

The following interview has been lightly edited for clarity.

CL: I’m curious how the format came about because it’s a pretty unique offering. How did you develop that?

AJR: It came about from a course I taught at NYU Shanghai in spring 2016, which was a global online course for all the sites. I developed it with the teaching and learning team out there and, at the time, Clay Shirky, who’s now the Vice Provost for Educational Technologies, had asked me to build an online course. We experimented a lot that semester! But I didn’t do an online course again until COVID-19 because up to that point I was in Washington Square and everything was in person.

One of the things that I had felt worked a lot back in 2016 was to break lectures up into mini-lectures rather than have one big long lecture over Zoom or video, which can be hard to pay attention to. So we thought, “okay, why don’t we do piecemeal videos for the class so students can watch one piece at a time, think about what they’re doing and practice with it, maybe go do something else, and then come back.” So, we divided what would normally be a 75-minute lecture into three short videos.

Being remote also means we can have shorter lectures because I don’t have to do the, “Remember your assignments are due this day” and “All of these other things that are these due others days,” speeches in each class! Instead, there is a big schedule that students can consult and then they complete the videos and the assignments on their own time, as long as they meet the deadlines.

In sum — we felt it doesn’t work as well to take a regular class and just move it online without revisions. We wanted to rethink the whole class from the beginning.

CL: It seems like part of it was designed by the necessity of being remote.

AJR: Right. So rather than say, “Oh, no we have to go online, how are we going to do it?” Let’s begin from the assumption that we’re online and figure out what’s the best version of that from the outset.

That said, I want to be clear I wasn’t the first to think of this!. A lot of research suggests there can be value to shorter videos for education in some circumstances. I mean, I’ve seen my own tolerance for a YouTube video. If it’s far more than five minutes I think to myself, “There’s no way I’m watching that.”

CL: Is there anything that surprised you about this first session now thatyou’ve been teaching it for a few weeks now?

AJR: This is the end of week three out of six and I’m maybe very unpopular today because it’s midterm day!

I will say — and I don’t know if this is just that summer students are really dedicated and engaged and that’s because they’ve chosen to study over the summer or something — but I’ve been just so impressed. The students seem really into it! It’s a very intense class anyway in a regular semester,and the fact that we’re taking 14 weeks and doing it in 6 means we’re going more than twice as fast, but all the students are doing great and asking great questions and seem engaged. During the regular academic year we normally have around 200 students. This summer, we only have about 60 so it’s smaller, so I actually get to interact with students one on one more than I do in an in-person class.

We’re also using all the other platforms, you know, Piazza and email and I have Zoom office hours that students come to and we discuss the course. So, I weirdly am interacting with more students individually than I normally do during the semester. I didn’t expect that.

CL: If you had a student who was on the fence about taking the course. What would be your pitch to them about why they should sign up?

AJR: Of course, I want to be sensitive to tuition costs, so I want to acknowledge first this does cost extra beyond regular academic year tuition. That said, I would say if a student is on the fence because they’re just not sure if that’s how to spend their summer and they’re thinking, “Oh, should I do this in the summer or the fall?” I will say that what’s cool about the summer is there’s a lot of value to just focusing on one class at a time and really diving deep. If it were me, and if cost isn’t an issue, I would take this class in the summer rather than the fall. Because being able to focus on this and then really look at the world around us through a data science lens is very powerful.

It’s also a smaller class size. So you’re actually going to get more attention from the TAs and from me than you would in the fall. I would say generally this course is for anyone who’s thinking, “What is data science? It seems important, but I don’t know what it is.”

I feel very strongly that anyone and everyone can succeed in this class. It’s designed so that you can walk away and continue your data science studies, if that interests you.

But it’s also a self contained course. So even if you just spend the six weeks with us, you’ll get enough so that you can leave and start doing your own data science projects or collaborate with others . You’ll be able to teach yourself more advanced things after the semester is over. We spend a whole unit on how to figure things out for yourself after this class is over and you can go out into the world with that knowledge. Being a Data Scientist is about a mix of thinking like a scientist and the more “tangible” skills, like programming and statistics. And we push both. The focus is on a foundation that you can go use right now.

An analogy I use at the start of class is: If I’m about to move to, for example, China for a year and I don’t have any idea how Mandarin works it’s going to be really hard to pick anything up and actually learn while I’m there. If I take a 101 class and go with a foundation for what is going on in this language, then I can start having even basic conversations and really pick things up. I think of Data Science for Everyone as the 101 class before you study abroad as a data scientist that will allow you to go out in the world and hit the ground running as someone who now thinks like a data scientist and has the skills to start doing their own research.

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NYU Center for Data Science
NYU Center for Data Science

Written by NYU Center for Data Science

Official account of the Center for Data Science at NYU, home of the Undergraduate, Master’s, and Ph.D. programs in Data Science.

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