Syllabus data

Academic year
2026Year
Term
Second Semester
Course title
Mathematical Analyses
Class type
Lecture
Course title (ENG)
Mathematical Analyses
Class code・Class name・Teaching forms
Z1900029 Mathematical Analyses
Instructor
TAKEKAWA Takashi
Credits
2.0Credits
Day and Time
Fri.3Period
Campus
Shinjuku Remote
Location
.,A-1441 Izumi12

Relationship between diploma policies and this course
A) A high degree of specialized expertise 80%
B) The skills to use science and technology 20%
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
・Understand and apply Bayesian inference
・Implement fundamental reinforcement learning algorithms
・Understand computational decision-making modeling
Prerequisites
[Requirements (preferable)]
Understanding of the basics of differential equations and probability statistics.
Method Using AL・ICT
Project Based Learning/Discussion Debate/Presentation/Interactive classes using ICT/Support for self-learning using ICT

Class schedule
1. Foundations of Computational Modeling
2. Reinforcement Learning
3. Parameter Estimation via Bayesian Inference
4. Model Selection
5. Analysis Using Computational Modeling
6. Model Extension
7. Advanced Topics

Evaluation
Grades will be based on presentations and reports in the lecture.
Feedback for students
The class will be conducted with questionnaires and dialogues to measure the level of understanding.

Textbooks
No designated textbook.
Reference materials
創造性の脳科学: 複雑系生命システム論を超えて、坂本 一寛 (著)、東京大学出版会、ISBN 978-4130633727

Office hours and How to contact teachers for questions
Monday 15:35-17:20, A-1516
Message for students
The content will differ significantly from previous years.

Course by professor with work experience
Applicable
Work experience and relevance to the course content if applicable
データ分析の経験がある教員が、実データに対する理論適用の経験を活かし、実践的な力学系理論の活用について講義する。

Teaching profession course
Informatics Program