Faculty overview

In the 5th Science and Technology Basic Plan (2016-2020), the Japanese government states that it will utilize data science knowledge to "share the vision of a 'super smart society' that brings prosperity to people as the vision of the future society, and further deepen a series of efforts to realize it, while strongly promoting it as 'Society 5.0', and realizing a super smart society ahead of the world." This "super smart society" is "a society in which the necessary things and services are provided to those who need them, when they need them, and in the amount they need, and various needs of society can be finely addressed, and everyone can receive high-quality services, and a society in which people can live vibrantly and comfortably, overcoming various differences such as age, gender, region, and language," and is expected to bring prosperity to people. In this context, Faculty of Data Science opened in Kumagaya City, Saitama Prefecture (Kumagaya Campus) in Reiwa 3 with the aim of producing a wide range of people, from those who have a deep understanding of data science to those who are conscious of applications in the real world and contribute to value creation in the modern economic society. Faculty of Data Science offers subjects in various fields related to data science, and provides education that is strongly linked to the practical work of each field. For example, in the business field, you can learn about the application of data science in the fields of finance and marketing. You can also learn more about the extensive use of data science in tourism, sports, government work, weather forecasting, and regional development.

Characteristics of undergraduate education

To study data science, you need a liberal arts mindset to discover problems from data and a science perspective to solve them using data. Faculty of Data Science offers a wide range of classes for both liberal arts and science. In the first year, students will learn general education, foreign languages, careers, sports and health, etc., which are the foundation of all learning, as well as the basics of specialized subjects (specialized basic subjects) that are the foundation of data science. From the second year, students will begin taking the "Basic and Advanced Subjects of Data Science" and the "Basic and Advanced Subjects of Value Creation." In the Basic and Advanced Subjects of Data Science, students will learn the basics of mathematics, statistics, information science, programming, etc., which are the foundation of data science, as well as advanced content that has been developed from these. In the Basic and Advanced Subjects of Value Creation, students will learn the basics of fields where data science is practically used (business, tourism, society, sports), and how to develop and use them more practically. In addition, there are also courses that allow students to directly come into contact with practical work such as fieldwork and internships, and by taking these courses, students can become more conscious of their own future. In addition, basic knowledge of mathematics is essential for studying data science. Our faculty offers supplementary classes outside of class hours for students who are not good at mathematics, to help them gain the academic ability and knowledge they need to study data science.

Characteristics and Initiatives of Faculty of Data Science

Faculty of Data Science is taking various measures to increase student satisfaction, not only in terms of academics and life during enrollment, but also in follow-up after graduation. Here, we will introduce some of the features of our faculty, focusing on the keywords "qualifications," "educational system," and "post-graduation collaboration."

• Back up various qualification acquisitions

  In Faculty of Data Science, students can obtain or take on a variety of qualifications. For example, by taking the teacher training course and earning credits, students can obtain a high school teacher's license (information). Students can also obtain a variety of qualifications, such as the appointment qualifications of "social welfare officer," "social education officer/social educator," and "museum curator," as well as the certification qualifications of "GIS academician," "social researcher/specialized statistical researcher," and "social researcher." In addition, we actively support students in obtaining various qualifications that will be useful in the future, such as the Information Processing Engineer Examination, IT Passport Examination, G-Test (Generalist Test), and Statistics Test, by opening special courses and introducing e-learning systems.

• Careful professional guidance from faculty members in their specialized fields

  In Faculty of Data Science, students are supervised by 25 full-time faculty members with a proven track record in various fields, including government agencies, sports, business, and tourism. In the specialized research (seminars) that begin in the third year, students are assigned to each faculty member's laboratory and receive intensive, specialized guidance. The results of their research are compiled into a graduation research project (research conducted by a group of multiple students) or a graduation thesis (research conducted by an individual). Graduation research and graduation thesis are a way of fully utilizing what students have learned during their four years at university, and can be considered the culmination of their studies.

• Practical education system in collaboration with companies and organizations

  Internships and fieldwork will be conducted in collaboration with companies and organizations that are actually developing business models using data. Through this, students develop the ability to respond to various social and economic issues, such as discovering issues and proactively proposing solutions to them.

• An open research and education system that allows collaboration even after graduation

  In order to keep up with the rapid technological advances in data science, we provide opportunities for graduates to return to the university to exchange information, acquire new knowledge, and receive the latest information. Additionally, we aim to build an education and research system that takes advantage of our network with alumni, such as dynamically changing the content of our education based on feedback from alumni and collaboration partners.

Objectives related to human resource development and other educational and research objectives / Educational goals / Three policies

Faculty of Data Science has the following objectives in terms of human resource development and other educational and research activities: to train talented individuals with a deep, flexible, and high moral character who can act as data analysis experts and contribute to discovering and using data to solve problems in modern society and the economy, and to conduct the education and research necessary for this.

In order to achieve this, we have established and published the following integrated set of "Educational Objectives," "Policy for Graduation Certification and Degree Awarding (Diploma Policy)," "Policy for Composing and Implementing the Educational Course (Curriculum Policy)," and "Policy for Accepting Students (Admission Policy)," as follows: