Academic Year |
2024Year |
School/Graduate School |
School of Informatics and Data Science |
Lecture Code |
KA301001 |
Subject Classification |
Specialized Education |
Subject Name |
データサイエンスセミナーI |
Subject Name (Katakana) |
データサイエンスセミナー1 |
Subject Name in English |
Data Science Seminar I |
Instructor |
MUKAIDANI HIROAKI,YANAGIHARA HIROKAZU,OGURA MASAKI,FUKUSHIMA MAKOTO,EGUCHI KOJI,YU YI,YAMADA HIROSHI,LI MENGMOU,NAGAHARA MASAAKI,SHIMA TADASHI,MONDEN REI,FURUI AKIRA,TING HIAN ANN,HIRAKAWA MAKOTO,NUNES TENDEIRO JORGE,ANDRADE SILVA DANIEL GEORG,AIZAWA HIROAKI,ADILIN ANUARDI,KAMEI SAYAKA,SUMIYA TAKAHIRO,MORIMOTO YASUHIKO,IWAMOTO CHUZO |
Instructor (Katakana) |
ムカイダニ ヒロアキ,ヤナギハラ ヒロカズ,オグラ マサキ,フクシマ マコト,エグチ コウジ,ユ イ,ヤマダ ヒロシ,リ メンモ,ナガハラ マサアキ,シマ タダシ,モンデン レイ,フルイ アキラ,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,アンドラーデ シルバ ダニエル ゲオルグ,アイザワ ヒロアキ,アディリン アヌアルディ,カメイ サヤカ,スミヤ タカヒロ,モリモト ヤスヒコ,イワモト チュウゾウ |
Campus |
Higashi-Hiroshima |
Semester/Term |
4th-Year, First Semester, 1Term |
Days, Periods, and Classrooms |
(1T) Inte |
Lesson Style |
Seminar |
Lesson Style (More Details) |
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Credits |
1.0 |
Class Hours/Week |
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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 |
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Special Subject |
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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. |
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Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students) | Informatics and Data Science Program (Knowledge and Understanding) ・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data.
(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.
(Comprehensive Abilities) ・D3. Ability to examine social needs and issues which are interlinked in a complex manner, using a top-down view to solve the problems through quantitative and logical thinking based on data, diverse perspectives, and advanced skills in information processing and analysis. |
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. |
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(More Details) |
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Learning techniques to be incorporated |
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Suggestions on Preparation and Review |
Ask the advise to your supervisor. |
Requirements |
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Grading Method |
Ask the advise to your supervisor. |
Practical Experience |
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Summary of Practical Experience and Class Contents based on it |
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Message |
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Other |
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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. |