| Academic Year |
2025Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA309001 |
Subject Classification |
Specialized Education |
| Subject Name |
データ科学セミナーI |
Subject Name
（Katakana） |
データカガクセミナー１ |
Subject Name in
English |
Data Science Seminar I |
| Instructor |
DOHI TADASHI,EMURA TAKESHI,YAMADA HIROSHI,SHIMA TADASHI,MONDEN REI,TING HIAN ANN,HIRAKAWA MAKOTO,NUNES TENDEIRO JORGE,ADILIN ANUARDI,MUKAIDANI HIROAKI,KAMEI SAYAKA,SUMIYA TAKAHIRO,MORIMOTO YASUHIKO |
Instructor
(Katakana) |
ドヒ タダシ,エムラ タケシ,ヤマダ ヒロシ,シマ タダシ,モンデン レイ,ティン ヒェン アン,ヒラカワ マコト,ナヌッシュ テンデイル ジョージ,アディリン アヌアルディ,ムカイダニ ヒロアキ,カメイ サヤカ,スミヤ タカヒロ,モリモト ヤスヒコ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
4th-Year, First Semester, 1Term |
| Days, Periods, and Classrooms |
(1T) Inte |
| Lesson Style |
Seminar |
Lesson Style
(More Details) |
Face-to-face, Online (simultaneous interactive) |
| |
| Credits |
1.0 |
Class Hours/Week |
|
Language of Instruction |
B
:
Japanese／English |
| Course Level |
4
:
Undergraduate Advanced
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
4 year student |
| Keywords |
Literature search、Reading academic papers and/or books、Programing、Data analysis |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | The seminar is positioned as a preliminary seminar before starting the graduate research. |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Data Science Program
（Knowledge and Understanding）
・D1. Knowledge and ability to understand the theoretical framework of statistics and data analysis and to analyze qualitative/quantitative information of big data accurately and efficiently.
（Abilities and Skills）
・D2. Ability to take charge of organizational strategy and planning based on statistical evidence by making full use of a wide range of knowledge and techniques in data science.
（Comprehensive Abilities）
・D3. Ability to overlook social needs and issues that are intertwined in a complex manner and to solve issues with quantitative and logical thinking based on data, a multifaceted perspective, and advanced information analysis ability. |
|---|
Class Objectives
/Class Outline |
Students learn the following skills under the guide by the supervisors: Literature search、Reading academic papers and/or books、Programing、Data analysis. |
| Class Schedule |
lesson1 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson2 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson3 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson4 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson5 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson6 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson7 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson8 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson9 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson10 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson11 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson12 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson13 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson14 Literature search、Reading academic papers and/or books、Programing、Data analysis
lesson15 Literature search、Reading academic papers and/or books、Programing、Data analysis |
Text/Reference
Books,etc. |
Ask the advise to your supervisor. |
PC or AV used in
Class,etc. |
Text, Visual Materials, Microsoft Teams |
| (More Details) |
|
| Learning techniques to be incorporated |
Discussions, Project Learning |
Suggestions on
Preparation and
Review |
Ask the advise to your supervisor. |
| Requirements |
|
| Grading Method |
Ask the advise to your supervisor. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| 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. |