Broad knowledge and solid expertise
Becoming a person who can lead to comprehensive solutions

　The faculty's curriculum is based on the two axes of "Data Science Subject Group" and "Cultural Cluster Subject Group", and is characterized by its well-balanced composition of the humanities and sciences.

　Professor Hisahiro Yado, who has designed data science education at the same department, talks about the distinctive curriculum as follows. “While many data science faculties adopt curricula that emphasize so-called science subjects, in this faculty you will study liberal arts and science subjects without bias. We aim to create “comprehensive knowledge.”

　Comprehensive knowledge is the fusion of all kinds of "knowledge" including natural science, humanities, social science, etc., and the power to create new value from it.The Cabinet Office is also promoting its importance as a source of innovation in the society of the future.

　Let's take a closer look.In the "Data Science Course Group" where you learn research methods and theories in the Faculty, "Data Analysis Course", "Basic Mathematics Course", and "Information/Computer Course" are systematically arranged into basic, applied, and advanced. We will improve our expertise in data science.

　In addition, the “Cultural Cluster Courses” for understanding the cultures that are the subject of research include “Cultural Resources Courses” for studying history and literature, “Language Data Science Courses” for studying language, and the mechanisms of human behavior. Subjects such as "behavioral data science subjects" are arranged to broaden knowledge about culture.

　From the third year, students belong to laboratories with 3 diverse themes, and deepen their learning according to their own interests.In her compulsory PBL-type course "Joint Research", she uses data science methods to analyze actual cultural content and refine her practical skills.

　“In our laboratories, we are engaged in a wide variety of initiatives. Some laboratories engage in joint research with private companies and work with local governments to solve specific problems. At the same time, we regard them as companions who grow together, and we are promoting research activities together.”

　In addition, in the "experience-based liberal arts course", many programs in collaboration with companies where graduates are active, such as lectures by lecturers invited from companies and internships, are incorporated so that students can envision their future goals.

　He says that there are two major career directions that can be envisioned after learning these things.

　"One is a 'developer' who has mastered the methods of data science. They pursue careers that make use of their expertise, such as going to graduate school and working in research and development, or working as a data scientist at an IT vendor or manufacturer.

　The other is "high-level users" who can utilize their knowledge of data science in their own work.Even if you don't have a job directly related to data science, you can make use of what you've learned in this department to see things from a bird's-eye view and play an active role as a person with the ability to analyze things numerically."

　“Data science can handle any theme, and is truly a field of study that achieves diversity and inclusion in research. Acquisition of comprehensive knowledge through data science will lead us to the age of humans. I want him to become a person who can lead the way," says Professor Sukuhisa with great expectations.