Data Science as a Major

I can honestly say that I have never told anyone that I was a data science major without an immediate response of, "What does that mean?" (And I've never really known exactly how to explain data science.) As this continues to happen throughout my career here at Bryant, I came to the decision that there are many people that belong in the data science major, but do not know enough about it in order to realize that for themselves. There are very few faculty members that know about data science, and they present differing information on what classes are best to take or what career path to choose. Because of the unfathomable amount of uncertainty that is associated with the major of data science, I decided to reflect on my experience so far and everything that I wish I knew a few years ago. 

As an incoming freshman, I had a lot of trouble deciding on which major I wanted to take up here at Bryant. All I knew was I really enjoyed math and considered myself a Microsoft Excel expert. I could have easily fit into a major of accounting, finance, or some sort of mathematics. Luckily, I have a few family members with experience in computer science and analytics that recognized my interested and recommended that I see how I fit in to data science. I knew within a week of taking an introduction to programming course that I had made the right decision. Learning different programming languages was something I never considered before in high school, as I didn't realize how closely it related to mathematic formulas and statistical analysis. And programming is only one aspect of data science. Other students in my major may prefer machine learning or artificial intelligence, and they are able to take classes based on those focuses instead. Data science has many different areas of opportunity, and there are various career paths that can be chosen based on which aspect someone wants to work with.

Here at Bryant, the data science program is relatively new, so the curriculum changes every year. Because of this situation, academic advisors and most professors may not always know which classes you are required to take and the order that they should be taken in. The best thing to do when trying to make your schedule is reach out to a faculty member that you know is a part of the data science program or one of the older students. We realize that many freshman are unsure of what to do and receive very little guidance, as we were in the same place a few years ago. This is why any student with a question about data science or even considering looking into the program should contact one of the upperclassmen or the Bryant DSA Instagram page. Everyone understands that it can be confusing and will be happy to help. Some of the best advice I got going into the program was from the seniors that were graduating from the program at the time. As it works for many other things, the most efficient way to find answers to your questions is to look to someone that just went through the same experience. 

Overall, there are so many opportunities that can come from choosing this major. On top of this, it will only continue to expand as this newly created field continues to develop. It is absolutely worth it for anyone that is looking into a mathematics, analytics, or computer-related major to explore what data science has to offer. And most importantly: never hesitate to reach out. No matter what path you choose, there will always be someone available and excited to share their own experiences and offer guidance. 

 

 

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