Harshvardhan is studying financial economics at the Gokhale Institute of Politics and Economics in India. He taught himself R using DataCamp to give himself an extra advantage, and recommended DataCamp to his professors. The Institute started using DataCamp in Computational Finance courses to help get students up to speed.
Tell us a little about your background.
I am doing a Master's in financial economics at the Gokhale Institute of Politics and Economics in India. For my undergraduate degree, I did a Bachelor's of commerce from the University of Delhi.
I didn't have any previous experience with data science. I took a year gap after my undergrad to prepare—In India it is a different system, you have to take an entrance exam for graduate programs. So while I was preparing for that, I decided to do a few courses on R, and discovered DataCamp.
Why data science?
I knew that I wanted to get into economics. In economics, one major subject is econometrics, which is all about statistics and data analysis. I thought, why not add something that is to my advantage, and learn to code.
How has learning to code given you an advantage?
Well, learning to code gave me an edge in my class. I already knew how to code and use R, which made writing my computational finance paper much easier. For empirical analysis, we use statistical software quite frequently in projects and the classroom, and with big data and machine learning, everyone is moving towards R and Python, so it is really beneficial to learn to code. I'll be graduating soon, and with knowledge of coding it will be a lot easier to be better at my job as a Forecasting Analyst. As an analyst, I'll apply all the analysis techniques we have studied, like time series analysis, to actual client-based projects. Rather than having to learn on the job, I think having a prior background in coding and data science will be a powerful added advantage to me.
What do you like about DataCamp?
I am not from a programming background. I didn't know computer science or anything. I hadn't done any coding before. When you do an introductory course on DataCamp, it teaches you the logic behind every single thing. For me, even something as simple as a for loop was a bit difficult to understand at first. DataCamp breaks it down so well, so that you get the intuition and the logic behind it.
Other sites have a whole lot of videos and not a lot of practice. That is the best part about DataCamp: short videos, they give you the tutorials, then you can practice on your own. They tell you, "there is an error on this line." That feature is pretty cool.
DataCamp is a lot better than other online learning platforms I've tried. It takes less time, it is more efficient, and you get hands-on practice. You are literally coding and trying it on your own. I would say it is better than any other platform for learning R and Python.
How has DataCamp helped you in your classes?
In my masters program, we have tons of subjects where we have to do data analysis. Our university was registered with the DataCamp for the Classroom program. I was probably the first student on the campus that was aware of DataCamp and how good it is. When the professors used to teach computational finance, they didn't use to teach us a whole lot of programming because that wasn't their job. They were telling us how to apply the theory. So we missed out on the basic things. It was more about just remembering how to write a program, and just memorizing it. So that made things less intuitive and required a lot more effort.
Then I thought, DataCamp has a lot of introductory courses as well as courses on computational finance, so I introduced it to my professor and told her, "maybe we should do this." It is better for the students to learn the basics of programming so they could do the classwork more efficiently. Then she made an account and registered our class for DataCamp for the Classroom.
How have your professors utilized DataCamp?
Our professor is a PhD. in Finance. She has a lot experience, but she isn't that efficient at teaching programming. So I thought, if everybody did introduction to R or Intermediate R, that would be great. They would understand these functions very well. So I was just browsing the DataCamp website and I came across this tool, DataCamp for the Classroom. If you sign up a class, it is absolutely free. So I talked to her, and she registered for that and invited all the students. Our grading system for computational finance is we have a final exam that is 60%, then we have two assignments that constitute 20% each. One of those assignments, 20% of the final grade, was based on how well you perform on selected courses on DataCamp. We did Introduction to R, Introduction to Portfolio Analysis in R, and Introduction to Computational Finance in R.
What advice do you have for new learners on DataCamp?
The intro courses are pretty interesting. If you start the introductory course, you just have to be consistent with it. I think it applies to learning anything well—you have to be consistent with it. If you do a course, then you stop using R, or stop coding for a month or so, then you pretty much forget how to do everything. So the one thing I think people should do is be consistent with it. Do the practice courses, practice what you already know, to make things less hazy in your mind.
I have gone back to courses a few times. If I get stuck doing a project, I can quickly go back and remember how to use a particular function, or figure out what syntax error I am making by using DataCamp courses.
And finally, I think you should learn your basics first. Just looking up answers on other sites and copy and pasting the answers won't be helpful in the long term.
Update from the DataCamp team: Harshvardhan completed his degree and is now working in the data analytics field, building price forecast models. Congratulations, Harshvardhan!