Fundamentals of System Science

Academic unit or major

Undergraduate major in Systems and Control Engineering

Instructor(s)

Masahiro Takinoue / Isao Ono / Masayuki Yamamura / Shogo Hamada

Class Format

Lecture (Face-to-face)

Media-enhanced courses

-

Day of week/Period
(Classrooms)

7-8 Tue (S4-203(S423)) / 7-8 Fri (S4-203(S423))

Class

-

Course Code

SCE.A302

Number of credits

200

Course offered

2025

Offered quarter

3Q

Syllabus updated

Sep 17, 2025

Language

Japanese

Syllabus

Course overview and goals

This course provides students with a wide range of skills of basic mathematical science that is necessary to system design and control.

Course description and aims

At the end of this course, students will be able to understand the basics of various mechanisms behind systems,
And furthermore, lay the groundwork for the expertize acquisition.

Keywords

Intelligent Systems, Artificial Intelligence, Machine Learning, Complex Systems, Evolutionary Computation, Molecular Robots, Molecular Computers, Engineering Biology

Competencies

• Specialist skills
• Intercultural skills
• Communication skills
• Critical thinking skills
• Practical and/or problem-solving skills

Class flow

Professors in the department who are conducting advanced research in the field of computational intelligence and systems science will give lectures about systems and mathematical science form diverse perspectives.

Course schedule/Objectives

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

Text book specified by the instructor.

Reference books, course materials, etc.

All materials used in class can be found on LMS.

Evaluation methods and criteria

Students' course scores are based on homework.

Related courses

• CSC.T272 ： Artificial Intelligence
• ZUS.I301 ： Introduction to Artificial Intelligence
• ICT.H318 ： Foundations of Artificial Intelligence (ICT)
• CSC.T353 ： Biological Data Analysis
• ART.T548 ： Advanced Artificial Intelligence
• ART.T556 ： Molecular Robot Informatics

Prerequisites

No prerequisites.

Other

Lectures are subject to changes.