SEMINAR B(2)

Once you log in, you can use the following functions (Keio ID required).
Affiliation information (faculty, department/major, year level, etc.) is set in the search criteria (available to new students after enrollment).
Favorite (Bookmark)
View syllabus details

Lecturer(s)	FURUTANI, TOMOYUKI
Credit(s)	2
Academic Year/Semester	2025 Fall
Day/Period	Mon.3
Campus	SFC
Class Format	Face-to-face classes (conducted mainly in-person)
Registration Number	26059
Faculty/Graduate School	POLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Year Level	1, 2, 3, 4
Field	RESEARCH SEMINARS SEMINARS
Grade Type	This item will appear when you log in (Keio ID required).
Prerequisites(Recommended)	B3101 統計基礎/INTRODUCTION TO STATISTICS B3211 ベイズ統計/BAYESIAN STATISTICS B3210 統計解析/STATISTICAL ANALYSIS
Related Classes	B3205 環境ガバナンスのデータサイエンス/DATA SCIENCE FOR ENVIRONMENTAL GOVERNANCE
Recommended Knowledge	B3205 環境ガバナンスのデータサイエンス/DATA SCIENCE FOR ENVIRONMENTAL GOVERNANCE
Location	SFC
Course Requirements	This item will appear when you log in (Keio ID required).
Student Screening Courses requiring entry to selection should be registered via SOL-A. *Only students who have a CNS account and who are not students of the Faculty of Policy Studies, Faculty of Environment and Information Studies, Graduate School of Media and Governance, Faculty of Nursing and Medical Care, and Graduate School of Health Management can enter via the system. Please check K-Support News for the details.	This item will appear when you log in (Keio ID required).
Equipment & Software	R, Python
Contact(Mail)	This item will appear when you log in (Keio ID required).
K-Number	FPE-CO-05003-211-88

Course Administrator	Faculty/Graduate School	FPE	POLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Course Administrator	Department/Major	CO
Main Course Number	Level	0	Faculty-wide
	Major Classification	5	Research Seminars
	Minor Classification	00	Seminar
	Subject Type	3	Elective subject
Supplemental Course Information	Class Classification	2	Lecture
	Class Format	1	Face-to-face classes (conducted mainly in-person)
	Language of Instruction	1	Japanese
Academic Discipline		88	Comprehensive / Integrated Areas (Interdisciplinary Studies)

Course Summary

Under the theme of "Data Science and Society," this workshop aims to deepen students' understanding of evidence-based problem solving by using data science methods to address social issues of interest to them.

Course Description/Objectives/Teaching Method/Intended Learning Outcome

In the seminar, we will mainly have readings and exercises to learn statistical analysis methods and AI, and individual research presentations by the students.

Research Seminar Theme

Data scientist: The sexiest job of the 21st century (2)