Syllabus

SubjectHEURISTIC COMPUTING

Class Information

Faculty/Graduate School
POLICY MANAGEMENT / ENVIRONMENT AND INFORMATION STUDIES
Course Registration Number
44840
Subject Sort
C2071
Title
HEURISTIC COMPUTING
Field
Advanced Subjects - Series of Environment And Information Studies
Unit
2 Unit
Year/Semester
2025 Fall
K-Number
Year/Semester
2025 Fall
Day of Week・Period
Wed 3rd
Lecturer Name
Class Format
Face-to-face
Language
Japanese
Location
Class Style
*Please click here for more information on the correspondence between 'Class Style' and ’Active Learning Methods’.
GIGA Certificate
Not applied

Detail

Course Summary

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We would like to provide knowledge on some practice in data analysis.

In the practical data science process, modern machine learning models and statistical models are only one element of the entire business process.
It is important to utilize these technologies in the multiple knowledge accumulated in the field of business in the past.
In this course, this process is interpreted as “Heuristic Computing”.

The following contents are not dealt with in this course:
- Theory and Implementation of Modern Machine Learning Algorithms / Statistical Models
- How to improve the performance of machine learning models.
- Business Model using AI