Faculty of Data Science

Department of Data Science

Data Science?

Nowadays, it is common sense to analyze data and constantly formulate new strategies in a wide range of fields such as business, healthcare and welfare, and administration.
To that end, you must always develop the power of "finding issues," "collecting information," "analyzing," and "finding new knowledge."
Data science is an "information science" that has a systematic theory, but it is also a practical study that is indispensable for business.
Human resources who have acquired data science to solve problems through statistical thinking based on data, so-called "data scientists", are expected to play an active role in all fields around the world in the future.

Feature 1

Sales and service industries…

We analyze customer information, purchase history, Web site browsing history, etc., and propose "products that are likely to be purchased" to users on the site.
When distribution companies deliver goods to various locations, we analyze delivery volume, location, time, number of trucks, weather and traffic information, etc., and formulate a delivery plan that optimizes costs and time.

Feature 2

In the medical field,…

Analyzing the vast amount of medical data accumulated at hospitals, it is useful for early detection, prevention and treatment of illness while reducing the burden on doctors and nurses as much as possible.
By analyzing medical big data, we search for genetics and substances that cause disease and contributes to the creation of new drugs.

Policies to be fostered and diplomacy policy of graduation and degree

Shimonoseki City University Faculty of Data Science develops human resources who can contribute to the creation of new value by learning theories and practices related to mathematical statistics, intelligence and social sciences necessary for design, analysis and utilization of diverse data.

A.: Through knowledge of statistics and related mathematical sciences, and the experience of analysis utilizing them, he acquires the ability to collect, organize, and analyze data and logically consider the knowledge obtained from it.
B.: Having knowledge about algorithms such as information management and analysis and artificial intelligence, and through the experience of expressing them on computers, acquire the ability to analyze and utilize various forms of data and handle them appropriately. I have.
C.: By learning how data analysis is performed in the field of business or healthcare, along with the knowledge unique to each field, we understand the role that data can play in society and have the necessary ethics and sense of responsibility (moral).
D.: Appropriate communication can be carried out in cooperation with various people, and the statistical interpretation of the analysis method used and the statistical interpretation of the results can be conveyed in an easy-to-understand manner.

Curriculum policy for organizing and implementing curriculum policy

Faculty of Data Science organizes and implements a curriculum based on the following policies so that students can acquire the knowledge and skills of the Diploma Policy.

A.: After acquiring the basic knowledge of mathematics related to data science from one to two years, and in the next few years, acquire lecture subjects and exercise subjects to acquire a wide range of knowledge and skills related to statistical analysis techniques.
B.: After acquiring basic knowledge on information and programming in 1-2 years, after 2 to 3 years, lectures and exercise subjects to acquire a wide range of knowledge about algorithms including artificial intelligence and data analysis and utilization skills. Learn subjects.
C.: In the next few years, acquire subjects to learn data analysis in the field of business or healthcare. At the same time, through lectures and active learning-type subjects, students will acquire ethics and responsibility as a technician handling data.
D.: Throughout the first to fourth years, acquire exercise subjects, project-type learning subjects, and graduation research to acquire communication skills, presentation skills, and creative thinking skills.
E.: In order to ensure objectivity and strictness, the evaluation of Gaku Osamu achievements, the degree of achievement of the goals of each class described in Shirabass will be used to evaluate the degree of achievement of each class subject described in Shirababus in order to ensure objectivity and strictness.

Specialized Education Curriculum

		1 year	2 years	3 years	4 years
Exclusively Gate Base Foundation	Mathematics and Information Systems	Mathematics Fundamental Information Society and Ethics Linear Agentology Informatics Overview Introduction to DS Programming Probability theory	Analyticals Database Geometrics Mathematical Statistical Network Technology Theory Algorithm theory
	Introduction to DSF	Introduction to Data Science Introductory Data Science	Data Science Fundamental Data Science Exercise Information and occupation
	Use of data analysis		Quantitative data analysis Regression analysis Categoryical data analysis Table data actuarial analysis Datahandling Explanation of artificial intelligence Chronological analysis Bayes Statisticals	Quantitative data analysis exercises Statistical modeling Categoryical data analysis exercises Table data mathematical analysis exercises Data marining Machine learning Digital Signal Processing Technology Statistical Social Studies Law Text-mining Pattern recognition Social Network Analysis Statistical Social Research Law Exercise Data analysis exercises
	Exercise and Graduation Research	Colkyam I	Research Ethics	DS Project Colkyam II	Graduation research
Exclusively Gate Oh, Use	Business Data Science		Management Information Overview Information system theory Management Information Systems	Operations Research Marketing research E-commerce theory Maritime Optimization Business Data Analysis
Exclusively Gate Oh, Use	Health data Science		Epidemiology and Public Health Sciences Health and Medical Sciences Overview	Essentialology Overview Pharmacology Overview Sensitive data processing Medical Health Information Sciences Bioinformatics Clinical Research Overview Biological statistics

※The curriculum is subject to change.

Introduction of class subjects

Explanation of artificial intelligence

Artificial Intelligence is an essential basic technology that supports the foundation of living. The technology and services are rapidly spreading in various aspects of life and work, such as economy, medical care, education, politics, arts, sports, and games. In order to understand the technology currently called artificial intelligence, we will systematically learn basic technologies and specific applications, and also conduct programming exercises as an issue.

DS Project

In the DS project, small groups will discuss, analyze, and present presentations in all areas: Statistical, Business Data Sciences, and Health Data Sciences. In the form of Project-based learning (PBL / problem-solving learning), while handling real data, you will find issues yourself and learn how to solve them.

Marketing research
<Business field>

Marketing Research is an analysis that solves problems related to management strategies and marketing activities. Acquisition skills that can be used in business through group work, using actual products and services as examples.

Biological statistics
<Health field>

In biostatistics, students will acquire statistical science, data science consulting matters that are useful for medical research such as cancer research. We will also implement issues on a small group level and acquire overall know-how in data analysis in medical research.

Expected course

After graduation, you will be able to use your expertise in data science to engage in planning and marketing, system engineers in a wide range of industries, or in healthcare-related work at public institutions and medical institutions.

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

Acquisitions and Qualifications

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

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

Lecture Block D

On the first floor, there is a classroom where a large number of people can take lectures and exercises, and a student resting space, and a teacher's laboratory are located between the second and fourth floors. If you have any questions, we have realized the short distance between students and teachers, where you can consult immediately. At the same time, a promenade on the campus will be developed, and the campus will be reborn as a beautiful campus where you can spend your university life comfortably.

Q&As

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 study 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 literary 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, you will learn the basics of mathematics related to data science as a "specialized basic subject". 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. In particular, the university is expected to learn practically on the two pillars of "Business Data Science" and "Health Data Science", and will be active as planning, marketing analyst, SE, etc.