Our university has established the Mathematics, Data Science, and AI Education Program (applied basics level) as a university-wide undergraduate education program. This program is an applied basics program that follows the Mathematics, Data Science, and AI Education Program (literacy level), and provides education to understand the basic concepts and methods of data science and AI by studying application examples.

Ministry of Education, Culture, Sports, Science and Technology Mathematics, Data Science and AI Education Program Certification System (Applied Basic Level)

This program has been certified under the Ministry of Education, Culture, Sports, Science and Technology's "Mathematics, Data Science and AI Education Program Certification System (Applied Basic Level)" (certification valid until March 12, 3).

• Ministry of Education, Culture, Sports, Science and Technology "Mathematics, Data Science and AI Education Program Certification System (Applied Basic Level)"
• Contents of application to the university's accreditation system

1.Name and outline of the educational program

(1) Name

"Mathematics, Data Science,AIEducational Program (Applied Basic Level)

(2) Outline

As a university-wide undergraduate education program,AIAn educational program (applied basic level) will be established and a certificate of completion will be issued to those who complete the program. 　This program is focused on mathematics, data science,AIThis is a program on applied basics following the educational program (literacy level), and by learning application examples,AIThis course provides training to help students understand the basic concepts and techniques of the technology.

2.Course subjects and completion requirements

Mathematics, Data Science,AIThe "Introduction to Data Science" course, which is a requirement for completing the educational program (literacy level),A(1Units) and Introduction to Data ScienceB(1In addition to having acquired the "credits" required for completion of the program, students will be deemed to have completed the program when they meet the following requirements. In addition, students may take courses outside of their own department through the course registration system offered by other faculties and departments.

Class subject	Departments	school year	unit	Completion requirements	Remarks
Data Science (※)	Department of Marine Environmental Science	3	2	Acquire credits by completing two courses.
Data Science (※)	Undergraduate Course of Logistics and Information Engineering	3	2		If you are taking courses in other faculties or departments, you can take the course in your second year.
Data Science Exercises (2023(Students enrolled before the current academic year)	Undergraduate Course of Logistics and Information Engineering	2	1	Acquire credits by completing two courses.	If you are taking classes in other faculties or departments, you can take the class remotely.
Data scienceAIPractice (2024(Students enrolled after the academic year)		2	2

3.Abilities that students can acquire

(1) "Introduction to Data Science"A(Part related to applied basic level)

1. Understand the significance of learning data science.
2. Understand the evolution of AI and its technical background.
3. Understand rights and ethics when applying AI.

(2) "Introduction to Data Science"B(Part related to applied basic level)

1. Understanding the fundamentals of data analysis
2. data·AIUnderstand the basics of programming required for utilization

(3) "Data Science"

Understand the basic concepts and methods of data science by studying application examples.

1. Understand the significance of learning data science.
2. Be able to select appropriate data analysis and visualization methods depending on the purpose of analysis.
3. Based on the analysis results, you can understand the background and meaning of the events that are occurring. 

(4) "Data Science AI Practice"

By studying application examples, you will understand the basic concepts and methods of AI.

1. Understand the overview of technologies for collecting, processing, and storing data.
2. Understand the basics of data representation for handling data on a computer. 
3. Understand the basic concepts of machine learning, deep learning, and reinforcement learning.
4. Be able to explain examples of AI services/systems that combine multiple AI technologies.

Five.Results of self-inspection and evaluation

• FY2024 Self-Inspection and Evaluation Report