Hiroshima University Syllabus

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Japanese
Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA226001 Subject Classification Specialized Education
Subject Name 医療・福祉政策とデータ解析
Subject Name
(Katakana)
イリョウ・フクシセイサクトデータカイセキ
Subject Name in
English
Data Analysis for Medical and Welfare Policies
Instructor DOHI TADASHI,OKAMURA HIROYUKI,RAYTCHEV BISSER ROUMENOV
Instructor
(Katakana)
ドヒ タダシ,オカムラ ヒロユキ,ライチェフ ビセル ルメノフ
Campus Higashi-Hiroshima Semester/Term 3rd-Year,  First Semester,  Intensive
Days, Periods, and Classrooms (Int) Inte
Lesson Style Lecture Lesson Style
(More Details)
 
This course is an internship-type course held during five days in the summer vacation and gives a practical experience of the research/development conducted
in industry to students.  
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 4 : Undergraduate Advanced
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students Third Year Students
Keywords practical course, computer science, data science, intelligence science, internship-type course 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
 
Criterion referenced
Evaluation
Informatics and Data Science Program
(Abilities and Skills)
・D2. Ability to develop strategies and plans for an organization based on statistical evidence by using a wide range of knowledge and skills related to data science.
 
Class Objectives
/Class Outline
``Data Analysis for Medical and Welfare Policies'' is replaced by ``Project Study'' from 2022.

This course is an internship-type course held during five days in the summer vacation and gives a practical experience of the research/development conducted
in industry to students.

 
Class Schedule Lessons 1-3: Guidance
Lessons 4-6: Seminars
Lessons 7-9: Introduction of project provided by a company.
Lessons 10-12: Research and development
Lessons 13-15: Summary of the results, preparation of the report and presentation material, presentation.

In 2022, ``Project Study'' will be hosted by Mazda Inc. This lecture is in principle held in the headquarters building of Mazda, Hiroshima city. In the emergency case due to the COVID-19, the face-to-face lecture style may be switched into the online style.

In this course, each student selects one of two themes in advance.  


No exam. but some reports may be given.


Theme:
① Development of a visualization application with automobile data:
The purpose of this project study is to learn the development method  of modern web application which consists of front-end and back-end, where the ideas of the application are discussed from the viewpoint of users. In the workshop within the project, students learn the pair-programming technique and experience the team development of the application with the automobile data.
② Application of machine learning to manufacturing premise:
We deal with two problems; the label classification of temper tire, and the anomaly detection with welding time-series data, by means of the machine learning, where the both data are measured in the actual
manufacturing process of Mazda. We discuss the selection of machine
learning methods, pre-processing of the data, model development, training of machine learning, and assessment methods, and derive the optimal model for the above projects.
 
Text/Reference
Books,etc.
No text book 
PC or AV used in
Class,etc.
 
(More Details) The PC and some media info will be provided.  
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
The skill sets requested for each project are given by

① Any programming language has to be used in this theme. Also, the experience
to have used SQL(Structured Query Language)including SELECT statement and
WHERE clause.
② The Python language will be used in the theme. Also, the experience to
use Keras, PyTorch,OpenCV,scikit-learn is appropriate.

To learn the skill sets for each theme, we will provide the on-demand materials
for self-study, so students are requested to learn them in advance.  
Requirements The upper limit of the number of course students is 18, where eight and ten students will be assigned for the theme ① and ②, respectively. If more than 18
students registered this course, we select exactly 18 students based on their
GPA and experiences of the skill sets.
 
Grading Method The grade evaluation for credit will be made by not only the practitioners in the company but also the faculty stuffs in Hiroshima University, based on the participation status in the project, attitude towards the task, achievement in research and development, presentation, etc.
 
Practical Experience Experienced  
Summary of Practical Experience and Class Contents based on it Through the internship-style course during 5 days, we will provide a practical course to learn the knowledge, skills and sense in application required in industry. The course materials are sufficiently discussed by both the company and university.  
Message In the project study, the sensitive data measured in the company may be used, so students may be requested to sign on a nondisclosure agreement. Without doing this, students cannot attend the course.  
Other The transportation expense to the headquarters building of Mazda, Hiroshima city, has to be paid by students themselves.  
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. 
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