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

Faculty of Data Science

Department of Data Science

Established in April 2024

Create the world with "1 byte" rough stones

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

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

New school building Lecture Block D

Notice

Information

What is Data Science?

We are now in Japan and overseas, as well as in a wide range of fields such as business, healthcare and welfare, and administration.
It is common sense to analyze data and always make new strategies.
To do so, we usually find issues, collect information, analyze them, and find new knowledge.
You have to nurture your power.
While it is an "information science" with a systematic theory.
Data science is also an integral part of business and other activities.
Human resources who have acquired data science that solves problems through statistical thinking based on data.
The so-called "data scientists" are expected to play an active role in all fields around the world in the future.

In the sales and service industries…

We analyze customer information, purchase history, 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, the burden on doctors and nurses is reduced as much as possible, and is useful for early detection, prevention, and treatment of diseases.

Human Resources to Develop and Diploma 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 is awarded to human resources (data scientists) with the following four qualities (A to D):

Through knowledge of statistics and related mathematical sciences, and experience of analysis utilizing them, students acquire the ability to collect, organize, and analyze data, and logically consider the knowledge obtained from them.

Through his knowledge of algorithms such as information management and analysis, artificial intelligence, and his experience of expressing them on a computer, he acquires the ability to analyze and utilize various forms of data and handle them appropriately.

By learning how data analysis is performed in the fields of business or healthcare, along with the unique knowledge of each field, students understand the role that data can play in society and acquire the ethics and sense of responsibility (morals) necessary for handling data.

It is possible to communicate appropriately with various people, and to communicate the analytical methods used and statistical interpretation of the results in an easy-to-understand manner.

Characteristics of curriculum <educational curriculum>

Features of the Curriculum

Our curriculum <educational curriculum> consists of three pillars: basic education, liberal arts education, and specialized education.
In the first and second years of Shimonoseki City University "Faculty of Data Science", students study mathematical statistics and information science mainly as basic subjects in data science. From the second year onwards, we will develop practical skills by setting up courses in Business Data Science and Health Data Science as specialized applied subjects. In addition, by taking foreign language education courses, liberal arts courses, career education courses, etc. as basic education and liberal arts courses common to all universities, we will train data scientists who can acquire rich culture and excellent employment skills, and utilize various data to create new value and solve various issues in each field.

Curriculum to develop practical skills through business and health

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

	1st year	2nd year
Professional Basics	Mathematics and Information Students acquire knowledge of mathematics, informatics, statistics, programming and algorithms.
	Introduction to Data Science and Basics Understand the flow of data science and acquire basic skills and thinking methods.
		Utilization of data analysis Students acquire a wide range of knowledge and skills in various analytical methods.
	Exercise and Graduation Research Students acquire communication skills, presentation skills, and creative thinking skills.
Specialized applications		Business Data Science Learn how to use data for management of various companies and organizations.
Specialized applications		Health Data Science Learn how to use data to achieve a healthy life for people.

Example of course model

Basic education for cultivating the basics of learning and morals at university, liberal arts education with a wide range of knowledge to play an active role in society, specialized basics for learning the basics for enhancing the expertise of data science, and specialized applications for learning the knowledge and skills necessary for applying in the real world. We will use a personal computer as a must-have and develop classes that utilize it.

1st year Spring Semester

	Month	Fire	Water	Tree	Money
1st contract				Academic literacy
2nd period	Business Administration	The Constitution of Japan	English	Industry and Mirai in Shimonoseki	Basic Mathematics
3rd period	Introduction to Data Science	Information Society and Information Ethics	Sports practice
4th period			Literature		English
5th period		The laws of nature

Example of Spring Semester in the Third Year

	Month	Fire	Water	Tree	Money
1st contract	Machine learning		Marketing research	Categorycal Data Analysis Exercise
2nd period	Data mining	E-commerce Theory			Sensitivity Data Processing
3rd period			Operations Research
4th period	DS project			Statistical Social Survey Act	Quantitative Data Analysis Exercise
5th period

The expected course

After graduation, he is expected to leverage his expertise in data science to engage in business related to healthcare in a wide range of industries, as a planning, marketing, system engineer, or at public institutions and medical institutions.

Example of course destination

● Manufacturing, retail, advertising, and publishing
● IT and telecommunications
● Administration
● Health and medical institutions (including university hospitals)
● Research Institute think tank
● Pharmaceutical companies
● Financial institutions (banks, insurance, securities, etc.)
● Graduate school, etc.

Qualifications available

The following licenses and qualifications can be obtained by acquiring the prescribed credits (selection system).

● Junior high school teacher type license (math)
● High school teacher type license (math)
● High school teacher type license (information)
● Social Investigators

Admission Policy (Admission Policy)

Admission Policy

Based on the image of human resources to be trained, in addition to basic knowledge and skills, the Graduate School has established the Admission Policy as follows in order to accept human resources with abilities such as thinking, judgment, and expression, as well as independence, diverse students, and collaborative skills.

A	Basic knowledge and skills required to learn data science include mathematics and foreign language knowledge learned at high schools, etc.
B	Being interested in daily social issues as abilities such as thinking, judgment, and expression skills, problem discovery and solution skills to think about solutions using data, communication skills that allow the team to think about better proposals through exercise classes, etc.
C	As 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 local communities.

Q&As

Question and Answer

Q I was a liberal arts student in high school, can I learn data science?: A
Data scientists can aim regardless of humanities or sciences. In the first place, data science is a discipline that analyzes data and creates new value while utilizing theories such as mathematics, statistics, machine learning, and programming. To do so, it is necessary to understand society, economy, and human beings, and a humanistic sense is useful.
Q I'm not very good at mathematics. Can I keep up with the class?: A
You need a minimum level of math knowledge, but you don't necessarily need advanced math knowledge. After enrollment, you will learn the basics of mathematics related to data science as a "specialized basic subject". We are also preparing a system for remedial learning.
Q What kind of fields can you play an active role after graduation?: A
Human resources capable of utilizing massively accumulated big data will be required in a wide range of fields, both public and private sectors. In particular, at the university, students are expected to learn practically in the two pillars of "Business Data Science" and "Health Data Science", and be active as planning, marketing analyst, SE, etc.