Overview of Data Science: an Educational Program in Mathematics, Data Science, and AI
Understanding How “Data” is Essential to Modern Society
In the midst of the current Fourth Industrial Revolution, society is undergoing major changes toward achieving Society 5.0, a super-smart, human-centered society following the hunting, industrial, and information societies. The curriculum for data science at Sophia University is based on MDASH-Literacy, an approved educational program for mathematics, data science, and AI established by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) to provide all university students with the fundamentals of mathematics, data science, and AI, the “reading, writing, and arithmetic” of the digital society required for such changes.
Features of University-Wide General Studies Course: Overview of Data Science
Overview of Data Science was launched in fiscal 2020 as a university-wide elective course to help students understand how data is used in work and daily life today, how it can be used, and what the challenges are. From the 2022 academic year, it has become a university-wide required course, which all first-year students are required to take. The course is positioned as an introductory course in the data science subject group, and content learned in this course will be further developed through subsequent developmental courses.
Students will grasp the overall picture of data science, rather than the basic knowledge that serves as an entry point. Students will learn about the use of AI and data science in a variety of settings, including daily life, business, and public policy, using video materials jointly developed for “Overview of Data Science” in collaboration with companies actively utilizing AI and data science in their work.
Overview of Data Science covers a wide range of methods used in statistics, data mining, and machine learning with an overall objective to learn when and how these methods and their results are used rather than to understand the mathematics of each method. Therefore, high school mathematics is not required to take Overview of Data Science and course content is easy to learn for first-time students in the humanities.
Students will deepen their understanding of important topics related to data science, regardless of academic discipline, including issues like laws and ethics. Students will learn about international trends surrounding data such as privacy laws, OECD guidelines, EU Data Protection Directive, Consumer Privacy Bill of Rights, and GDPR, as well as examples and ramifications of information leakage, data bias, algorithmic bias, and more.
The Learning Management System (LMS) is used to view video materials, browse lecture materials, comment on and ask questions about classes, and submit assignments and feedback. As such files and records are stored on LMS, students can reflect and review their learning outcomes at any time.
Program Courses and Completion Requirements
- Courses applicable to the 2022 academic year
For all faculties, completion of the program is based on the acquisition of two credits from the following course:
- Applicable for fiscal year 2021
In all faculties, completion of the program is based on the acquisition of 2 credits in one of the following courses:
- Applicable for fiscal year 2020
In all faculties, completion of the program is based on the acquisition of two credits in the following two courses:
Review and Verification Structure, Background, and Future Plans
As part of the long-term plan “Grand Layout 2.1,” Sophia University started to examine a renewal of the university-wide general education courses from the fiscal 2019, aiming to develop an educational system that meets the needs of the new era. In particular, Data Science has been established and deeply studied as one of the main pillars of the new university-wide general education system. In addition, pilot courses have been offered from fiscal 2020, prior to the new curriculum (mandatory subjects) starting in fiscal 2022; verification work, including a close examination of content and methods, has also been conducted. For details, please refer to the PDF file below.
Opinions, Results, and Initiatives for Improvement in the Self-Assessment System
We are improving the content of the Overview of Data Science course through successive verification (self-inspection and evaluation). Please refer to the following PDF file for details on the status of opinion hearings and improvements in previous years.