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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Systems and Control Engineering
- Instructor(s)
- Ishii Hideaki Aonishi Toru Ono Isao Takayasu Misako Takinoue Masahiro Deguchi Hiroshi Miyake Yoshihiro Yamamura Masayuki
- Class Format
- Lecture (ZOOM)
- Media-enhanced courses
- Day/Period(Room No.)
- Tue7-8(S621) Fri7-8(S621)
- Group
- -
- Course number
- SCE.S302
- Credits
- 2
- Academic year
- 2020
- Offered quarter
- 3Q
- Syllabus updated
- 2020/9/18
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course provides students with a wide range of skills of basic mathematical science that is necessary to system design and control.
Student learning outcomes
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
Machine Learning, Artificial Intelligence, Complex Systems, Intelligent Systems, Intelligent Robots
Competencies that will be developed
| ✔ 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/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Prof. M. Takayasu | Homework specified by the instructor. |
| Class 2 | Prof. M. Takayasu | Homework specified by the instructor. |
| Class 3 | Assoc. Prof. T. Aonishi | Homework specified by the instructor. |
| Class 4 | Assoc. Prof. T. Aonishi | Homework specified by the instructor. |
| Class 5 | Assoc. Prof. I. Ono | Homework specified by the instructor. |
| Class 6 | Assoc. Prof. I. Ono | Homework specified by the instructor. |
| Class 7 | Assoc. Prof. H. Ishii | Homework specified by the instructor. |
| Class 8 | Assoc. Prof. H. Ishii | Homework specified by the instructor. |
| Class 9 | Prof. H. Deguchi | Homework specified by the instructor. |
| Class 10 | Prof. H. Deguchi | Homework specified by the instructor. |
| Class 11 | Prof. Y. Miyake | Homework specified by the instructor. |
| Class 12 | Prof. Y. Miyake | Homework specified by the instructor. |
| Class 13 | Prof. M. Yamamura | Homework specified by the instructor. |
| Class 14 | Prof. M. Yamamura | Homework specified by the instructor. |
Out-of-Class Study Time (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 OCW-i.
Assessment criteria and methods
Students' course scores are based on homework.
Related courses
- ZUS.I301 ： Introduction to Artificial Intelligence
- ICT.H318 ： Foundations of Artificial Intelligence (ICT)
- CSC.T272 ： Artificial Intelligence
- ART.T548 ： Advanced Artificial Intelligence
Prerequisites (i.e., required knowledge, skills, courses, etc.)
No prerequisites.
Other
Lectures are subject to changes.
