| Academic Year |
2026Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA133001 |
Subject Classification |
Specialized Education |
| Subject Name |
情報処理と産業 |
Subject Name
（Katakana） |
ジョウホウショリトサンギョウ |
Subject Name in
English |
Information Processing and Industry |
| Instructor |
OKAMURA HIROYUKI,KUSHIOKA KATSUAKI,KAKUNO MINA |
Instructor
(Katakana) |
オカムラ ヒロユキ,クシオカ カツアキ,カクノ ミナ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
2nd-Year, First Semester, 1Term |
| Days, Periods, and Classrooms |
(1T) Mon5-8：ECON B155 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
Face-to-face |
| Omnibus Style in each day |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
J
:
Japanese |
| Course Level |
1
:
Undergraduate Introductory
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
Third Year Students |
| Keywords |
Practical Course, Digital Transformation (DX) |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Computer Science Program
（Knowledge and Understanding）
・C1. Knowledge and ability to work on problem-solving after understanding that various issues existing in human beings, society, and individuals can be interpreted in multiple ways depending on social conditions and culture.
Data Science Program
（Knowledge and Understanding）
・C1. Knowledge and ability to work on problem-solving after understanding that various issues existing in human beings, society, and individuals can be interpreted in multiple ways depending on social conditions and culture.
Intelligence Science Program
（Knowledge and Understanding）
・C1. Knowledge and ability to work on problem-solving after understanding that various issues existing in human beings, society, and individuals can be interpreted in multiple ways depending on social conditions and culture. |
|---|
Class Objectives
/Class Outline |
In this course, we invite practitioners/managers from seven major companies in local,
and summarizes the current progress and practical examples in computer science, data
science and intelligence science, which are demanded in industry and society. We discuss
the accelerated digital transformation (DX) performed in industry and learn how to utilize
the knowledge and skill acquired in the university courses to the industry. |
| Class Schedule |
Session 1: Course Guidance
We will explain how the course will be conducted, including information about reports and assignments. Attendance is mandatory.
Sessions 2 & 3 — Monday, April 20
Otafuku Holdings Co., Ltd.
“Digital Challenges as Envisioned by the Otafuku Group”
Sessions 4 & 5 — Monday, April 27
JFE Steel Corporation
“Utilization of Information Science at JFE Steel”
Sessions 6 & 7 — Monday, May 11
The Chugoku Electric Power Co., Inc.
“Digital Talent Sought by Power Companies and DX Case Studies”
Sessions 8 & 9 — Monday, May 18
Satake Corporation
“Information Processing and Industry: Satake’s Technical Requirements and Vision for Digital Transformation”
Sessions 10 & 11 — Monday, May 25
Mazda Motor Corporation
“Use of Digital Technology, AI, and Data in the Automotive Industry”
Sessions 12 & 13 — Monday, June 1
Micron Memory Japan, Inc.
“Information Utilization in Manufacturing: Advanced Data Analytics and Applications in Cutting‑Edge Semiconductor Memory Fabrication Facilities”
Sessions 14 & 15 — Monday, June 8
TOPPAN Inc.
“Solving Regional Issues Through Digital Technologies”
Need to complete the report for each lecture. |
Text/Reference
Books,etc. |
Text books will not be used. |
PC or AV used in
Class,etc. |
Handouts, Microsoft Teams, moodle |
| (More Details) |
|
| Learning techniques to be incorporated |
Discussions |
Suggestions on
Preparation and
Review |
No preparation is required, but the review of the contents for each lecture may be needed to complete the report. Handouts may not be provided in terms of the information protection in each company, so students should take notes in each lecture. |
| Requirements |
|
| Grading Method |
All reports have to be submitted by the due dates. Students are requested to attend all lectures. |
| Practical Experience |
Experienced
|
| Summary of Practical Experience and Class Contents based on it |
This course is given by practitioners in local industry. |
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |