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How to Explore Data Science if You Are Currently Studying Something Else

Six ways for students to gain skills, experiences, and connections to become a data scientist.

Image Credit: Keira Burton on Pexels
Image Credit: Keira Burton on Pexels

You have come across the fascinating world of data science and are excited about pursuing a career in it. But sadly, you are studying chemistry/ psychology/economics, etc., and can not pivot to a field of study that is more closely related to data science. You might feel limited by your circumstance, but as a student in a higher education institution, you have access to resources that can be building blocks for your data science dreams. Colleges and universities provide you with opportunities to gain an education, experiences, and connections, all of which can be helpful to an aspiring data scientist. The methods presented in this story are of little to no additional cost beyond your tuition. Whether you have a semester or several years left in your degree, it is not too late to take advantage of opportunities presented at your College/university and tailor them to your data science aspirations.

Gain an Education

Perhaps the most apparent reason for anyone to pursue higher education is to gain relevant knowledge in a field of their interest. However, many degrees are customizable allowing you to take classes outside of your department. With some planning, you could pursue a concentration, a minor, or stand-alone classes to build basic Data Science skills.

Photo by Shubham Sharan on Unsplash
Photo by Shubham Sharan on Unsplash

Pursue a concentration or a minor in data science

This option may be time restrictive due to how much additional time you have to complete your degree, but pursuing a minor or a concentration in data science can be an excellent way to gain foundational skills.

As data science is an interdisciplinary field and data is playing an increasingly critical role in a growing number of industries, more and more college majors are offering data science concentrations/options. Pursuing this can be an easier way to incorporate data science into your Education, and you can also see how your current field of study intersects with data science.

If your current degree does not have a concentration, you could look into pursuing a minor if that is available to you at your college or university. Unlike most concentrations, data science minors are typically more interdisciplinary, allowing you to take courses from multiple departments (ex: the University of British Columbia, the University of Washington, the University of Pennsylvania). Aside from learning foundational data science knowledge pursuing a minor can allow you to take an intriguing class you might be previously unaware of.

Take classes that will help you gain data science skills

If a minor or concentration is unavailable to you, you can take stand-alone classes that will help you gain the same skills. To figure out what courses to take, use a data science program’s curriculum or one of the many bootstrapped data science learning guides published on Medium.

Data Science Learning Guides:

A Complete Data Science Roadmap in 2021

Create Your Own Data Science Curriculum

Data Science Curriculum

Even if you can not take every suggested class, just having some basic programming and statistics knowledge can give you a functional level of data literacy. You can build on these skills after you complete your degree through graduate school, online courses, boot camps, or self-directed projects.

Gain Experiences

It’s time to take what you have learned outside of the classroom. As a college/University student, you have opportunities to apply your learning through joining a research project or as part of a student organization. The nature of what is available to you depends on your specific institution but, these opportunities are hard to come by once you have graduated so, it’s best to take advantage of them now.

Photo by Leon on Unsplash
Photo by Leon on Unsplash

Join a research project

In this excellent video, Tina Huang, a data scientist working at a FAANG company, shares the best data science project for students to pursue: researching with a professor.

With traditional personal projects, you are often working alone. Also, chances are if you are doing a project recommended by the internet, plenty of other people are doing it as well.

Companies want collaborative data scientists who do meaningful work with impact. When you are working on a professor’s research project, they have already done the hard work of finding a substantial question to answer with societal impact. You will also gain experience working on a team, which is always a plus.

Another benefit is that professors usually do not need someone with a full suite of data science skills. You can be a valuable team member with basic programming and statistics experience.

You can find research projects in the following two ways:

  1. Find professors who are doing captivating research that is relevant to your career goals. Cold email them. Tina recommends starting with your department and then branching out to other fields especially, biological sciences, economics, or business. These fields can have a lot of data to analyze and, it’s usually easier to learn the relevant subject matter on the job than it is to learn data science.
  2. If your college or university provides one, look through a database of research projects requesting research assistants who are experienced in or are interested in working with data.

If you are in the position to develop your own research project, you can try to incorporate data science work into your project as well.

Join a Technical Student Organization or Competition

Aside from research projects, universities often have plenty of organizations in which students work on technical projects. These are usually associated with the natural science, engineering, math, and computer science departments.

Getting involved in one of these organizations can be a great way to apply your data science skills. They can also be very interdisciplinary so you will likely meet and work with students from many different backgrounds. In my experience, I have noticed student teams tend to have fewer gatekeepers and allow younger students to participate more frequently so you may have an easier chance of joining one.

To find the best opportunity for you, make sure you share your goals and data science interests with the leaders of the organizations you are interested in.

Gain Connections

Networking is crucial for every career, and data scientist is no exception. As a college/university student, you have a built-in network of students, faculty, and alumni who can help you learn more about data science and life as a data scientist.

Photo by LinkedIn Sales Solutions on Unsplash
Photo by LinkedIn Sales Solutions on Unsplash

Join a Professional Organization

Professional organizations and societies exist to foster connections, share exciting research and discoveries, and support their members’ professional success. Joining a professional organization can help you meet other data scientists and learn more about the latest trends in the industry. Some organizations will also have sizable discounts for college/university students or have student chapters with discounted membership.

Data Science Professional Organizations and Societies:

Use your Student Card to Network

Networking can seem scary as a student, but professionals are more inclined to help students because they have been in the same situation. You can use LinkedIn to reach out to alumni of your university who are currently working as data scientists and ask for a 15-minute virtual informational interview. Not only will these give you more insight as to what it is like to be a data scientist but, if you regularly keep in touch, they might keep you in mind for referrals down the road.

Questions You Can Ask During Your Informational Interview:

  1. What do you like most/least about being a data scientist?
  2. How did you go about finding and applying to get your first data science (or related) role?
  3. How did your coursework and major prepare you for your current role?
  4. What classes do you recommend taking to do well as a data scientist?

Final Words

Pursuing any (or all) of these methods can be challenging alongside your regular coursework and other responsibilities. However, taking advantage of the opportunities available at your higher education institution can help solidify your data science ambitions and ensure this is a path you want to go on before any additional monetary investments. None of these steps will fully prepare you to become a data scientist but, they can give you a good foundation.

I wish you the best of luck in your data science journey!


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