Course Overview

Through a mix of lectures and hands-on practice, students will acquire the
knowledge and skills necessary to understand various problems in society
from a human-centered perspective and to solve them using AI and data
science. In this course, students will learn sparse modeling and robotics.

Learning Achievement

Through a mix of lectures and hands-on practice, students will acquire the knowledge and skills necessary to understand various problems in society from a human-centered perspective and to solve them using AI and data science. In this course, students will learn sparse modeling and robotics.

Competence

This lecture is related to "Utilization of Knowledge", "Management Abilities", "Research Abilities" and "Specific Knowledge" (Degree Programs in Systems and Information Engineering (Master's Program)).

Course prerequisites

Courses may be limited due to the nature of the exercises.
Priority will be given to students enrolled in the Human Centered AI curriculum in the Information Science and Engineering program.

Grading Philosophy

Grades are determined based on the content of the reports.

Course schedule

After lecture-style explanations by experts in each field, students will practice using real data and submit a report with the results. A detailed schedule will be announced via bulletin board and e-mail.
Sparse modeling for Materials informatics
In recent years, materials informatics, which uses data science in addition to experimental measurements and physicochemical calculations, has been actively studied in materials exploration. Among them is sparse

Course type

Lectures and Class Exercises

Online Course Requirement

Instructor

Kanamori Yoshihiro,Igarashi Yasuhiko,Yorozu Ayanori

Other information

A (laptop) PC will be used for exercises with real data.
The lecture will be given in English. Materials and data required for the lecture will be distributed through teams.

Site for Inquiry

Link to the syllabus provided by the university