Integrated Area / Data Science Program

Leveraging the characteristics of College of Arts and Sciences, this course serves as an entry point for learning the application of data science across a wide range of fields. This course covers the characteristics of each data environment and problem Area domain, the foundation for implementing analytical methods, an overview of analytical methods, and evaluation methods for application.

This course will cover various regression analyses and stochastic models using linear models that have developed alongside data analysis. Through lectures and exercises, you will learn about methods for obtaining models from data, as well as refinement techniques and evaluation metrics based on model plausibility.

I was originally interested in data analysis because I was in the science club in high school and used Excel. I'm a humanities student and I'm not good at calculations on paper. However, I realized that by understanding and applying functions in spreadsheet software, I could gain various insights from vast amounts of data, and I wanted to master data analysis. In the future, I want to become a data scientist. Even if I can't compete with people with a science background, I think that humanities students like me can fill in the gaps in areas where they struggle. As the name "science" suggests, data science requires taking science and math subjects. Some subjects are difficult for humanities students. However, the teachers make the lessons easy to understand with well-designed materials, so I feel very reassured.