Solving social issues through the fusion of literature and science.Characterized by practical specialized subjects in a wide range of fields

　So what are the features?In Japan as well, in the last year or two, the movement to create a cohesive education and research organization has begun with the keyword of data science instead of the conventional faculty of information science.There is already one national, public and private school, and we are probably the fourth in the country.This is the second private university.

　However, while each of the preceding universities focuses on approaches from the sciences (natural sciences), the university also allows approaches from the humanities (humanities / social sciences), focusing on fields close to interdisciplinary fields and applications. The feature is that you can learn "data science that leads to a career" by putting your feet on it and being more conscious of its utilization in society.With a large capacity of 240 people, we decided to accept not only science students but also liberal arts students, based on the profile of our students so far, with the image of developing human resources who can acquire data science and support society in the middle.

　Specialized subjects are "data science basic subjects" and "data science development subjects" to learn mathematics, programming, algorithms, the mechanism of the Internet, etc., and the latter are various such as "business", "tourism", "society", and "sports". It consists of "value creation basic subjects" and "data science practice subjects" for the fields (photos) [Fig. 1].Of course, you can study informatics, but for students who are not aiming to become a data science expert, you can use data science according to the theme you are interested in, the course you are aiming for, and the problem you want to solve. Have them take on the challenge of "value creation".

[Figure 1]

Of course, data science is related to all fields of society, so the career path after graduation covers all fields and occupations.Our goal is to be a "data scientist who is active in the field" who can support the programs and online environment required in each workplace, which are close to the field and useful in the field.Speaking of Fig. 2, it is the layer marked with a star, which is positioned as "human resources who can solve data science problems" and is considered to be the most shortage in the future.

[Figure 2]

As for faculty members, we have newly added OBs of central government offices and central banks such as the Statistics Bureau of the Ministry of Internal Affairs and Communications, the Cabinet Office, and the Bank of Japan, think tanks, and people with business experience in each field. We will also enhance practitioners.