Shimonoseki City University Faculty of Data Science Department of Data Science |

Faculty of Data Science

Department of Data Science

Opened in April 2024

Create the world with "one byte" rough stones

Provide diverse and free learning, along with data science knowledge and skills.
We will develop human resources who will lead us to the realization of a sustainable future.

Name of undergraduate/Department: Faculty of Data Science Department of Data Science
Capacity: 80 people (capacity: 320)
Period of study: 4 years
Acquisition degree: Bachelor of Data Science

New school building "Lecture Block D"

Notice

Information

What is Data Science?

Today, both in Japan and abroad, and in a wide range of fields such as business, health care and welfare, and administration,
It is common sense to analyze data and constantly formulate new strategies.
To that end, we will always find issues, collect information, analyze, and find new knowledge.
You have to feed the power.
Although it is an "information science" with systematic theory.
Data science is also a practical study that is indispensable for business.
Human resources who have acquired data science to solve issues through statistical thinking based on data.
The so-called "data scientists" are expected to play an active role in all fields around the world.

Sales and service industries…

We analyze customer information, purchase history, and website browsing history, etc., and propose "products that are likely to be purchased" to users on the site.

In the medical field,…

By analyzing the vast amount of medical data accumulated in hospitals, we use it for early detection, prevention and treatment of diseases while reducing the burden on doctors and nurses as much as possible.

Human resources to be trained and Diproma policy

Personnel to be trained and Diploma Policy

Faculty of Data Science at Shimonoseki City University develops human resources who can contribute to solving social and organizational issues and creating new value by mastering theories and practices related to mathematical statistics, informatics, and social sciences necessary to design, analyze, and utilize diverse data. Bachelor of Data Science will be awarded to individuals (data scientists) with the following four qualities (A to D).

Through his knowledge of statistics and related mathematical sciences, and his experience in analysis using them, he acquires the ability to collect, organize, and analyze data, and to logically consider the findings obtained from them.

He has knowledge of algorithms such as information management, analysis, and artificial intelligence, and through his experience of expressing them on a computer, he has acquired the ability to analyze, utilize, and properly handle various forms of data.

By learning how data analysis is performed in the field of business or healthcare, together with the knowledge unique to each field, they understand the role that data can play in society, and acquire the ethics and sense of responsibility (moral) necessary to handle data.

We can cooperate with various people to communicate appropriately and communicate the analysis methods used and statistical interpretation of the results in an easy-to-understand manner.

Characteristics of Curriculum

Features of the Curriculum

The curriculum of the university consists of three pillars: basic education, liberal arts education, and specialized education.
At Shimonoseki City University's Faculty of Data Science, students learn mathematical statistics and information science mainly in the first and second years. From the second year onward, we will establish a group of courses for "Business Data Science" and "Health Data Science" to develop practical skills. In addition, by taking foreign language education subjects, liberal arts courses, career education subjects, etc. as basic education and liberal arts subjects common to all universities, students will acquire rich culture and excellent employment skills, and utilize various data to develop data scientists who can create new value and solve various issues in the field.

Curriculum to develop practical skills through business and health.

Through lectures, exercises, and project-based learning subjects, students will acquire basic knowledge and skills in mathematics, information, and programming.
Particularly in the second to third years, students learn about "business data science" and "health data science" to develop specialized knowledge and practical skills.

	First Year	2nd year
Specialized foundations	Mathematics and Information Basics Students will acquire knowledge of mathematics, informatics, statistics, programming and algorithms.
	Introduction to Data Science and Technology Understand a series of data science and acquire basic skills and thinking methods.
		Use of data analysis Acquisition a wide range of knowledge and skills related to various analytical methods
	Exercise and Graduation Research Acquire communication skills, presentation skills, and creative thinking skills
Specialized application		Business Data Science Learn how to use data for the management of various companies and organizations.
Specialized application		Health Data Science Learn how to use data to help people live a healthy life.

Examples of models taken

Students learn by combining the basics of learning at university and basic education to nurture morals, liberal arts education with a wide range of knowledge to play an active role in society, specialized basics to enhance the expertise in data science, and specialized applications to learn the knowledge and skills necessary to apply in the real world. We will develop classes that utilize personal computers and develop classes that utilize them.

1st Annual Spring Semester

	Month	Fire	Water	Tree	Money
1st period				Academic literacy
2nd period	Business Administration	Japanese Constitution	English	Shimonoseki's industry and Mirai	Mathematics Basics
3rd period	Introduction to Data Science	Information Society and Ethics	Sports practice
4th period			Literature		English
5th term		The law of nature

3rd year of spring semester

	Month	Fire	Water	Tree	Money
1st period	Machine learning		Marketing research	Categorycal data analysis exercise
2nd period	Data mining	E.commerce theory			Sensitive Data Processing
3rd period			Operations Research
4th period	DS Project			Statistical Social Research Law	Quantitative data analysis exercise
5th term

Estimated course

After graduation, it is assumed that he will use his expertise in data science to engage in planning and marketing and system engineers in a wide range of industries, or in healthcare-related work at public institutions and medical institutions.

Example of course

● Manufacturing, Retailing, Advertising and Publishing
● IT and telecommunications industry
● Administration
● Health and Medical Institutions (including university hospitals)
● Research Institutes and think tanks
● Pharmaceutical Company
● Financial institutions (banks, insurance, securities, etc.)
● Entering graduate school

Qualifications to be acquired

The following licenses and qualifications can be obtained by predetermined credits (selection system).

● A junior high school teacher's license (mathematics)
● High school teacher type license (mathematics)
● High school teacher type license (information)
● Social Investigator

Policy for Accepting Admissions (Admission Policy)

Admission Policy

In this faculty, based on the image of human resources to be trained, in addition to basic knowledge and skills, as well as those with independence, diverse students, and collaboration as enrollees based on the image of human resources to be trained. Therefore, the advocacy policy was set as follows.

A	The basic knowledge and skills required to learn data science are mathematics and foreign languages to be studied at high schools.
B	The ability to think, judge, expressiveness, etc., who are interested in daily social issues and think about solutions using data to identify and solve problems, and communication skills that allow teams to think about better proposals through exercise classes, etc.
C	Independence, diversity, and collaboration, the attitude of learning with a sense of purpose, the ability to understand different cultures and values, and the public spirit obtained through activities in the local community.

Q&As

Question and Answer

Q I was a literature in high school, can I learn data science?: A
Data scientists are aimed at regardless of literature or science. In the first place, data science is a discipline that uses theories such as mathematics, statistics, machine learning, and programming to analyze data and create new value. To do so, you need an understanding of society, economy, and human beings, and a humanistic sense is useful.
Q I'm not very good at mathematics. Can I keep up with my class?: A
You need a minimum knowledge of mathematics for college exams, but you do not always need advanced math knowledge. After enrollment, students will learn the basics of mathematics related to data science as "Specialized Basic Courses". We are also preparing a remedial study system.
Q What kind of field will you be able to play an active part after graduation?: A
Human resources who can utilize the enormous accumulated big data will be required in a wide range of fields, both public and private sectors. Particularly at our university, students will learn practically through the two pillars of "Business Data Science" and "Health Data Science" and will be active as planning, marketing analyst, SE, etc.