Statistics × Data Science
Mai Suzumoto, 4th year student School of International Liberal Studies
Deepened knowledge in data science led to choosing my major
I am majoring in statistics at School of International Liberal Studies. When I first came across statistics in an undergraduate lecture, I became interested in data science, which is essential for its analysis. I remember being attracted to the fact that it can be used in a variety of fields, including economics, medicine, education, and politics. My professor was very kind, and as I asked him many questions after the lecture, I began to feel like I wanted to learn more.
I started taking lectures in the Data Science Education Program in my second year of undergraduate studies. In addition to my interest in School of International Liberal Studies was no longer an option. After acquiring knowledge of data science through the Data Science Education Program lectures, the statistics I was studying at undergraduate level seemed even more interesting, so I chose to take a statistics seminar at undergraduate level as well.
Suzumoto says that her hobby is illustration, and she enjoys uploading her illustrations to social media.
After learning data science, I learned about the impressions that change depending on the time of posting, the amount of text, etc.
I've become more aware of it.
Realize that you are acquiring skills through repeated practice
In the Data Science Education Program, students can take courses in stages, from the basics to practical content such as "Data Science of Regression and Classification" and "Data Science of Time Series Structure." The open courses are interesting because they offer classes in a variety of genres, but there are so many that it's difficult to choose, and I was a little worried that I wouldn't be able to see the connections if I just took whatever I was interested in. However, the Data Science Education Program provides guideposts on how to acquire knowledge, which is reassuring and motivating. I was also happy that it was easy to understand that certification was given for the number of classes taken, from literacy level to beginner level to intermediate level.
I'm originally a liberal arts student and I'm not very good at math, so there were times when I thought, "I don't understand 100%," and moved on. However, data science is a tool, so by using it many times, such as for assignment reports in undergraduate classes, you can suddenly understand it. Once you take the course, you can check the lecture content on your computer as many times as you like, which also helped me understand.
He belongs to a club that eats Chinese food, and is enjoying a fulfilling college life, both in his studies and in his leisure time.
Learning data science systematically gave me confidence
For my graduation thesis in the seminar I'm currently in, I'm researching real estate sales trends in Tokyo. I first became interested in real estate after watching an American reality show by chance. I was excited to see how customers were motivated to buy using various information about real estate, and how they were finally convinced and made the purchase. One day, I realized, "This is how we use data!"
However, when I actually started working on it, I found that the amount of data related to real estate was huge, and just interpreting the trends was quite hard work. First, I collected the data, divided and compared it by land, and once I found the variables, I further subdivided it... I just kept repeating this mundane work. What was particularly difficult was deciphering what people who actually purchase properties value and whether there were any changes in that. The data science education program not only taught me how to analyze, but also how to put the data into a form that can actually be used, which has been very helpful.
Originally, I didn't have a clear goal of "This is what I want to do!", so I chose a faculty where I could learn various things even after entering the university. After entering the university, while actually taking classes at the faculty, I began to think that it would be quite difficult to study in a systematic and deep manner because I could take subjects in various genres. I think that the Data Science Education Program is very attractive because you can deepen your knowledge of one academic field step by step. I think that there are many high school students who, like me, "still don't know what they want to do". Data science is a field of study that can be combined with any major, so if you learn it, it will be useful in an emergency.
In particular, I had a strong desire to avoid graduating with the regret that I hadn't accomplished anything at university, so I think it was good that I took the course, at least because it gave me the confidence to have acquired data science skills.
Being a liberal arts student, I often struggled with the content. However, as I studied in the data science education program, I began to find it fascinating that seemingly impersonal numbers can become practical just by arranging and organizing them according to certain standards. I plan to work as a systems engineer, so I hope to continue to use data in a way that is in line with reality and useful to people.
