| Academic Year |
2025Year |
School/Graduate School |
Graduate School of Integrated Sciences for Life (Master's Course) Division of Integrated Sciences for Life Program of Mathematical and Life Sciences |
| Lecture Code |
WG144051 |
Subject Classification |
Specialized Education |
| Subject Name |
数理計算理学特別演習Ａ |
Subject Name
（Katakana） |
スウリケイサンリガクトクベツエンシュウエー |
Subject Name in
English |
Exercises in Applied Mathematics and Computational Science A |
| Instructor |
HONDA NAOKI |
Instructor
(Katakana) |
ホンダ ナオキ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, First Semester, First Semester |
| Days, Periods, and Classrooms |
(1st) Inte：Faculty Office |
| Lesson Style |
Seminar |
Lesson Style
(More Details) |
Face-to-face, Online (simultaneous interactive) |
| Research project |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
B
:
Japanese／English |
| Course Level |
6
:
Graduate Advanced
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
01
:
Mathematics/Statistics |
| Eligible Students |
|
| Keywords |
|
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
To learn data-driven modeling of biological phenomena based on mathematical modeling and machine learning. |
| Class Schedule |
lesson1: seminar
lesson2: seminar
lesson3: seminar
lesson4: seminar
lesson5: seminar
lesson6: seminar
lesson7: seminar
lesson8: seminar
lesson9: seminar
lesson10: seminar
lesson11: seminar
lesson12: seminar
lesson13: seminar
lesson14: seminar
lesson15: seminar
none |
Text/Reference
Books,etc. |
Pattern Recognition and Machine Learning by Christopher M. Bishop |
PC or AV used in
Class,etc. |
Zoom |
| (More Details) |
|
| Learning techniques to be incorporated |
Discussions |
Suggestions on
Preparation and
Review |
Learn mathematical methods and biology in a well-balanced manner for applying them to their own research. |
| Requirements |
|
| Grading Method |
Evaluation is made based on the overall performance in the seminar talks and the outcome of graduation thesis.
|
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
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. |