Advanced Course of Information and Visualization

Academic year

2025Year

Term

Second Semester

Course title

Advanced Course of Information and Visualization

Class type

Lecture

Course title (ENG)

Advanced Course of Information and Visualization

Class code・Class name・Teaching forms

Z1000005 Advanced Course of Information and Visualization

Instructor

TACHIBANA Kanta

Credits

2.0Credits

Day and Time

Tue.2Period

Campus

Shinjuku Remote

Location

.,A-0511教室

Relationship between diploma policies and this course

A) A high degree of specialized expertise　100%
B) The skills to use science and technology　0%
C) The ability to conduct research independently, knowledge pertaining to society and occupations, and sense of ethics required of engineers and researchers　0%
D) Creative skills in specific areas of specialization　0%

Goals and objectives

Aim: to deeply learn information visualization
Goal: 1) understanding data visualization;
2) understanding visual perception of human;
3) knowing latest researches on information visualization

Prerequisites

A basic understanding of linear algebra and statistics.
Mastery of multivariate analysis, pattern recognition, machine learning and computational intelligence is not required, but students must listen to podcasts on these topics (Pattern Recognition Radio, Computational Intelligence Radio).

Method Using AL・ICT

Discussion Debate／Group Work／Presentation

Class schedule

Course Plan
Characteristics of Human Vision and Information Visualization
Data Visualization and Deep Concept Visualization
Measurement Scales of Variables and Information Visualization
Visualization of Data with Location Information
Verbalization, Diagramming, and Information Visualization
Strategic Use of Figures and Tables in Papers
The Essentials of Presentations
The Essentials of Poster Presentations
The Essentials of Oral Presentations
Conclusion: What and How Will You Visualize?

Preparatory Study
Use ChatGPT or other resources to acquire preliminary knowledge about topics that sparked your curiosity in the syllabus or previous classes.

Evaluation

Evaluated by discussions and report.

Feedback for students

Both in face-to-face class and online.

Textbooks

Podcast [Information Visualization Radio]

Reference materials

＜参考書＞
山本義郎・飯塚誠也・藤野友和、統計データの視覚化（Rで学ぶデータサイエンス12）、共立出版. ISBN 978-4-320-11016-8
Colin Ware, Information Visualization (Perception for Design) 3rd Ed., Morgan Kaufmann Publisher. ISBN 978-0-12-381464-7

Office hours and How to contact teachers for questions

Shinjuku campus A-1576, Wednesdays 14:00-15:00.

Message for students

Course by professor with work experience

Work experience and relevance to the course content if applicable

Teaching profession course

Informatics Program

Syllabus data