Faculty of Data Science Overview

In its 5th Science and Technology Basic Plan (FY2016-2020), the Japanese government stated that it would leverage the knowledge of data science to "share the vision of a 'super smart society' that brings prosperity to people as the future society, and further deepen a series of initiatives toward its realization, strongly promoting it as 'Society 5.0' and realizing a super smart society ahead of the world." This "super smart society" is defined as "a society that provides necessary goods and services to the right people, at the right time, and in the right amount, responding meticulously to the diverse needs of society, where everyone can receive high-quality services, and where people can live vibrant and comfortable lives, overcoming various differences such as age, gender, region, and language," and is expected to bring prosperity to people. Against this backdrop, Faculty of Data Science was established in April Reiwa 3 in Kumagaya City, Saitama Prefecture (Kumagaya Campus) with the aim of producing a wide range of individuals, from those with a deep understanding of data science to those who are conscious of its application in real society and contribute to value creation in the modern economic society. Faculty of Data Science offers courses in various fields related to data science, providing education that is strongly linked to practical applications in each field. For example, in the business field, students learn about the application of data science in finance and marketing. Data science is also used in tourism, sports, government work, and regional development, and students can learn about the utilization of data in these fields.

Characteristics of undergraduate education

Studying data science requires both a humanities-based approach to discovering problems from data and a science-based perspective to solve them using data. Faculty of Data Science offers a wide range of courses for both humanities and science students. In the first year, students learn general education subjects such as foreign languages, career development, sports, and health, which form the foundation of all learning, as well as the basics of specialized subjects that form the basis of data science (specialized foundation subjects). From the second year, students begin taking "basic and advanced data science subjects" and "basic and advanced value creation subjects." In the basic and advanced data science subjects, students learn the fundamentals of mathematics, statistics, information science, and programming, which are the foundation of data science, as well as advanced content that builds upon them. In the basic and advanced value creation subjects, students learn the basics of fields where data science is practically utilized (business, tourism, society, natural science, GIS, sports), and how to further develop and utilize them in a more practical way. In addition, there are courses that allow students to directly experience practical work, such as fieldwork and internships, and by taking these courses, students can become more aware of their own future.

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

  Faculty of Data Science offers opportunities to acquire or challenge various qualifications. For example, by completing the teacher training program and meeting the required conditions, students can aim to obtain a Class 1 High School Teacher's License (Information Technology). Students entering in 2026 and beyond can also obtain a Class 1 Junior High School Teacher's License (Mathematics) and a Class 1 High School Teacher's License (Mathematics). It is also possible to acquire a variety of certifications, such as the "GIS Academic Specialist" and "Social Survey Specialist." Furthermore, the faculty actively supports students in acquiring various qualifications that will be useful in the future, such as the Information Processing Technology Engineer Examination, the IT Passport Examination, and the Statistics Examination, by offering special courses and introducing e-learning systems.

• Careful professional guidance from faculty members in their specialized fields

  Faculty of Data Science offers instruction from full-time faculty members with proven track records in various fields such as government, sports, business, and tourism. From the third year, students participate in specialized research (seminars) within their respective faculty research labs, receiving intensive and specialized guidance. Research results are compiled as the culmination of four years of study. Students entering in 2026 and beyond will work on a "Graduation Research Project," while students entering between 2021 and 2025 will work on a "Graduation Research Project/Graduation Thesis."

• Practical education system in collaboration with companies and organizations

  The faculty offers its own internships in collaboration with companies and organizations that are actually developing business models using data. Through these internships, students will develop the ability to respond to various social and economic issues, such as identifying problems and proposing solutions to them on their own initiative.

• 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.

Introduction to Faculty of Data Science

• Department of Data Science

  Practical learning based on diverse fields: [Business / Society / Tourism / Natural Sciences & GIS / Sports]
  The curriculum is open to both science and humanities students. It includes a "Data Science Subject Group" that covers the application of AI, statistics, and programming, and a "Value Creation Subject Group" that covers the application of data science in business, society, tourism, natural science, GIS, and sports. A diverse group of faculty and staff with expertise in their respective fields will supervise your graduation research, allowing you to enhance your specialization in a research lab that aligns with your interests.

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:

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